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A WRF‐based high‐resolution reanalysis of the Irish climate (1981–2010) is used to create proxy daily precipitation observations at the locations of climatological sites used for precipitation monitoring; the data are statistically representative of the real precipitation climate both for mean (over monthly, seasonal and annual periods) and extreme values. The proxy observations are spatially interpolated to the original WRF grid using a typical gridding package and compared against the original data to assess gridding errors. The errors are more complex than the estimates provided by the gridding software; systematic biases are evident which by the inclusion of strategically placed additional observing sites are shown to be greatly reduced. There is also evidence of systematic differences in trend analyses of extreme precipitation over the period. The method provides independent estimates of the errors that arise from actual gridding applications. It also facilitates the testing of the optimality of a network by highlighting possible inadequacies in an existing station layout and suggesting new observing site locations to fill gaps. Uncertainties regarding the errors in real precipitation observations, and possible spurious impacts linked to temporal changes in the real observing network, are avoided by this method. [ABSTRACT FROM AUTHOR]

An early warning method based on Session Initiation Protocol (SIP) concept for generator set electrical control abnormal response is proposed. The first is to clean the electrical data of the generator set by SIP. Using Supervisory Control and Data Acquisition (SCADA) and Generalized Linear Models (GLM) algorithm, a linear model is constructed to analyze the electrical control of generating units. Using the Autoregressive Integrated Moving Average Model (ARIMA), an abnormal response early warning model for electrical control of generating units is established. BP neural network is used to train the abnormal response data of the generator set electrical control. According to the current response data, the model prediction is realized, and the early warning of the abnormal response of the generator set electrical control is effectively realized. The simulation results show that the proposed method can effectively reduce the early‐warning error, false alarm rate, and early‐warning delay of generator electrical control abnormal response. [ABSTRACT FROM AUTHOR]

Background Aims Samples and Methods Results Conclusions Interest in the potential of learning from errors to benefit innovation and organizational and personal growth is currently increasing. In practice, individuals frequently do not appear to learn spontaneously from errors and setbacks without support. Based on prior work, this paper considers antecedents and consequences of adaptive responses to errors.Two experiments with undergraduate students aimed to identify the causal link between beliefs and maintained motivation and the adaptation of actions to the end of analysing and effectively correcting errors.In Study 1 (N = 195, 72% female, M = 20.7 years, SD = 3.0), we experimentally manipulated learners' beliefs around the importance of errors to learning, after which they completed a 50‐min learning session on research methods and statistics. In Study 2 (N = 67, 58% female, M = 21.8 years, SD = 3.99), we intertwined the manipulation more closely with the actual learning process by using prompts about adaptive responses to errors immediately after error feedback.In Study 1, those to whom we stressed the negative effects of errors showed significantly fewer adaptive action‐related responses to errors, less persistence, and less use of metacognitive strategies after errors. In Study 2, we found significant positive effects on the learners' persistence, their metacognitive control, and effort investment.Our results support and expand previous, mostly correlational, research findings on individuals' adaptive responses to errors. [ABSTRACT FROM AUTHOR]

Background Aims Sample Method Results and Conclusions Many people fear failure and making mistakes. This fear can be transmitted from parents to children, suggesting that parental communication regarding failures and setbacks may play a critical role in shaping a child's perception of mistakes.In this study, we investigated how everyday parent‐child conversations about setbacks influence children's fear of making mistakes.Drawing on the large pre‐birth Growing Up in New Zealand cohort, we focused on a sub‐sample of 231 mother‐child dyads who engaged in a recorded conversations about a "recent disappointment or setback" when the children were 8 years old.Conversations between mothers and children about the recent disappointments were coded to identify whether parents recognised or acknowledge their child's emotional response, if action plans were discussed, and the types of resources that the child could draw on. The children also completed a questionnaire about their global self‐worth and their fear of making mistakes.The discussion of clear action plans, in the absence of a discussion about collaborative resources, was found to be associated with an increased fear of making mistakes among children. Conversely, when mothers clearly acknowledged their child's emotions and discussed ways to work collaboratively with their child on future problems, there was a notable decrease in the child's fear of mistakes. However, it is noteworthy that many mothers in our study either minimally acknowledged or dismissed their child's emotions(40%), rarely discussed action plans (55%), or collaborative resources (79%)when discussing the recent setback. [ABSTRACT FROM AUTHOR]

Copying information is vital for life's propagation. Current life forms maintain a low error rate in replication, using complex machinery to prevent and correct errors. However, primitive life had to deal with higher error rates, limiting its ability to evolve. Discovering mechanisms to reduce errors would alleviate this constraint. Here, we introduce a new mechanism that decreases error rates and corrects errors in synthetic self‐replicating systems driven by self‐assembly. Previous work showed that macrocycle replication occurs through the accumulation of precursor material on the sides of the fibrous replicator assemblies. Stochastic simulations now reveal that selective precursor binding to the fiber surface enhances replication fidelity and error correction. Centrifugation experiments show that replicator fibers can exhibit the necessary selectivity in precursor binding. Our results suggest that synthetic replicator systems are more evolvable than previously thought, encouraging further evolution‐focused experiments. [ABSTRACT FROM AUTHOR]

Background Aims Samples Methods Results Conclusion Students make many errors in visual programming. In order to learn from these, it is important that students regulate their emotions and view errors as learning opportunities.This study aimed to explore to what extent momentary emotions, specifically enjoyment, anxiety and boredom, as well as the error learning orientation of students, interacted during a 1‐day course on visual programming in an out‐of‐school learning environment.The sample consisted of 269 lower secondary school students (grades 7–9).The data were collected in an intervention study, with questionnaires applied directly before and after the course, and with four measurements of state emotions during the course.The results showed that error learning orientation had an expected effect on the students' emotions at the beginning of the course. The emotions changed positively over the course of the workshop, while the error learning orientation remained stable. No differences in error learning orientation were found between the control and intervention groups. An expected, reciprocal effect of students' emotions on their error learning orientation at the end of the course day could not be found.Changes in error learning orientation are difficult to achieve during 1‐day courses. Nevertheless, through targeted, pedagogical approaches, which aim to minimize the influence of unfavourable emotions that occur in problem‐oriented learning situations, teachers could help students develop a positive error learning orientation in the long term, whereby errors are viewed as an opportunity for learning. [ABSTRACT FROM AUTHOR]

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well‐known. However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration. Alpha and beta power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top‐down expectancies. When exploring the brain dynamics of feature integration, previous studies have only explored one frequency band. We explore if and how different cognitive failures can lead to incorrect feature integration by exploring the modulation of different frequency bands. Our results support that feature integration can go wrong at different stages including pre‐stimulus attentional processes (alpha), perceptual representations (post‐stimulus, alpha and beta), and working memory (gamma). [ABSTRACT FROM AUTHOR]

An 11‐year‐old, 500 kg, healthy mare was admitted for tenovaginoscopy. A jugular venous catheter was inserted to administer detomidine for diagnostic imaging and for anaesthesia‐related drug administration. The horse was premedicated with intramuscular acepromazine and intravenous flunixin. For sedation, 7.5 mL of a solution, presumed to be xylazine 2%, was drawn up in a syringe and labelled with a sticker. Two minutes after injection of 7.5 mL from xylazine‐labelled syringe, the horse showed severe ataxia and fell. Nystagmus and catatonia appeared while one person sat on its neck, to prevent it from rising. After 8 minutes, the horse could not be kept down and took several uncoordinated attempts to stand, still showing nystagmus and ataxia for several minutes. The xylazine‐labelled syringes were analysed. They contained pure ketamine. This case report should raise awareness about clinical errors, a healthy error culture and use of Morbidity and Mortality Rounds to improve patient and personnel care. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI)‐based diagnostic tools can offer numerous benefits to the field of histopathology, including improved diagnostic accuracy, efficiency and productivity. As a result, such tools are likely to have an increasing role in routine practice. However, all AI tools are prone to errors, and these AI‐associated errors have been identified as a major risk in the introduction of AI into healthcare. The errors made by AI tools are different, in terms of both cause and nature, to the errors made by human pathologists. As highlighted by the National Institute for Health and Care Excellence, it is imperative that practising pathologists understand the potential limitations of AI tools, including the errors made. Pathologists are in a unique position to be gatekeepers of AI tool use, maximizing patient benefit while minimizing harm. Furthermore, their pathological knowledge is essential to understanding when, and why, errors have occurred and so to developing safer future algorithms. This paper summarises the literature on errors made by AI diagnostic tools in histopathology. These include erroneous errors, data concerns (data bias, hidden stratification, data imbalances, distributional shift, and lack of generalisability), reinforcement of outdated practices, unsafe failure mode, automation bias, and insensitivity to impact. Methods to reduce errors in both tool design and clinical use are discussed, and the practical roles for pathologists in error minimisation are highlighted. This aims to inform and empower pathologists to move safely through this seismic change in practice and help ensure that novel AI tools are adopted safely. [ABSTRACT FROM AUTHOR]

Hydrologic signatures are quantitative metrics that describe streamflow statistics and dynamics. Signatures have many applications, including assessing habitat suitability and hydrologic alteration, calibrating and evaluating hydrologic models, defining similarity between watersheds and investigating watershed processes. Increasingly, signatures are being used in large sample studies to guide flow management and modelling at continental scales. Using signatures in studies involving 1000s of watersheds brings new challenges as it becomes impractical to examine signature parameters and behaviour in each watershed. For example, we might wish to check that signatures describing flood event characteristics have correctly identified event periods, that signature values have not been biassed by data errors, or that human and natural influences on signature values have been correctly interpreted. In this commentary, we draw from our collective experience to present case studies where naïve application of signatures fails to correctly identify streamflow dynamics. These include unusual precipitation or flow regimes, data quality issues, and signature use in human‐influenced watersheds. We conclude by providing guidance and recommendations on applying signatures in large sample studies. [ABSTRACT FROM AUTHOR]

Formative feedback is one of the most recognized types of feedback in academics. However, for feedback to be effective it must be task‐specific, immediate, corrective and positive. At present, automatic feedback is far from these characteristics and leaves the instructor as a fundamental agent in the teaching‐learning process of programming. Faced with this scenario, the lecturer needs support tools that help them to give formative feedback in educational scenarios with many students and little time. In this paper, we have demonstrated that, by using a tool called COLMENA, any lecturer may give students effective formative feedback which is task‐specific, immediate and corrective. COLMENA is a system that combines real‐time Eclipse IDE data retrieval on compilation errors and analytical dashboards in a webapp solution for lecturers and students. In this study, two different approaches have been compared, considering two academic courses with and without COLMENA feedback, respectively. The results indicate that novice students receiving feedback from the lecturer via COLMENA reduced their errors, demonstrating that feedback generated from compilation errors is effective. [ABSTRACT FROM AUTHOR]

The Consequence Argument is the classic argument for the incompatibility of determinism and our ability to do otherwise. Daniel C. Dennett objects that the Consequence Argument suffers from the same error as a clearly unconvincing argument that there are no mammals. In this paper, I argue that these arguments do not suffer from the same error. The argument that there are no mammals is unconvincing as it takes the form of a sorites, whereas the Consequence Argument does not. Accordingly, Dennett's objection misses its mark. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates a new approach for estimating the planning target volume (PTV) margin for moving tumors treated with robotic stereotactic body radiotherapy (SBRT). Methods: In this new approach, the covariance of modeling and prediction errors was estimated using error propagation and implemented in the Van Herk formula to form a Modified Van Herk formula (MVHF). To perform a retrospective multi‐center analysis, the MVHF was studied using 163 patients treated with different system versions of robotic SBRT (G3 version 6.2.3, VSI version 8.5, and VSI version 9.5) and compared with two established PTV margins estimation methods: The original Van Herk Formula (VHF) and the Uncertainty Estimation Method (UEM). Results: Overall, the PTV margins provided by the three formalisms are similar with 4–5 mm in the lung region and 4 mm in abdomen region to the PTV margins used in clinical. Furthermore, when analyzing individual patients, a difference of up to 1 mm was found between the PTV margin estimations using MVHF and VHF. The corresponding average discrepancies for the superior‐inferior (SI) direction ranged between −0.19 mm to 0.38 mm in CK G3 version 6.2.3, −0.36 mm to 0.33 mm in CK VSI version 8.5, and −0.34 mm to 0.40 mm in CK VSI version 9.5. Conclusions: It was found that for the lower left lung, upper left lung, lower right lung, upper right lung, central liver, and upper liver, the effect of covariance between model and prediction errors in SI direction was around 20%, 30%, 25%, 25%, 25%, and 30%, respectively. Notable covariance effects between model and prediction errors can be considered in PTV margin estimation using a modified VHF, which allowed for more precise target localization in robotic SBRT for moving tumors. Overall, in each of the three directions, the difference between MVHF and utilized clinical margins is 0.65 mm in the lung and abdominal region. Therefore, to improve the clinical PTV margins with the new approach, it is suggested to use the adaptive PTV margins in the next fractions. [ABSTRACT FROM AUTHOR]

Peri‐implantitis is a plaque‐associated pathologic condition occurring in tissues around dental implants, characterized by inflammation in the peri‐implant mucosa and subsequent progressive loss of supporting bone. It is a highly prevalent disease, as extensively estimated by large‐population, cross‐sectional studies. As peri‐implant diseases represent opportunistic infections, it is reasonable to assume that nonideal conditions, local and/or general, may favor the progression of peri‐implant inflammation. Some of these conditions could be a result of poor planning and/or inadequate execution of any step of the entire process treatment. This article describes the major possible factors in implant therapy that may lead to peri‐implantitis. For some of these (ie, inappropriate patient selection, insufficient periodontal therapy, lack of diagnosis and management of peri‐implant mucositis, erratic supportive peri‐implant/periodontal therapy) there is a good level of evidence, whereas for others (ie, wrong implant placement, poor postoperative care, inadequate prosthetic reconstruction, lack of assessment and management of peri‐implant soft‐tissue deficiencies) there is little scientific evidence. More research is therefore needed to clearly identify the errors and/or complications possibly leading to peri‐implantitis, particularly over the long term. [ABSTRACT FROM AUTHOR]

Different types of errors and complications may arise during and after the execution of periodontal or implant‐related procedures. Some of the most relevant, although also controversial, and less commented, causative agents of errors and complications are methodological biases and bad interpretation of the evidence. Proper assessment of the literature requires of solid clinical knowledge combined with a systematic approach built on the recognition of common methodological biases and the avoidance of interpretive errors to critically retrieve, dissect, and judiciously apply available information for the promotion of periodontal and peri‐implant health. This review addresses common types of methodological bias and interpretive errors that can alter the reader's perceptions on the real effect and potential ramifications of the reported outcomes of a given therapeutic approach due to bad interpretation of the available evidence: (1) types of methodological biases; (2) spin and interpretive bias; (3) interpretation pitfalls when assessing the evidence (4) choice of relevant endpoints to answer the question(s) of interest; and (5) balance between statistical significance and clinical relevance. [ABSTRACT FROM AUTHOR]

The occurrence of errors, complications, and adverse effects may occur as a consequence of single or multiple events related to the clinician and/or patient. Apparently, the amount of dental literature on these undesirable outcomes has not been as prolific as that obtained for conventional primary periodontal outcome measures. This review explores the potential reasons for the lack of studies reporting on errors and complications in periodontal and implant therapy, as well as other noteworthy methodological aspects, to enlighten their impact on the selection of the best (or most appropriate) "gold standard" periodontal/implant‐related treatment options, and on the overall decision‐making process. The following points were addressed: (a) the importance of reporting errors and complications in clinical research; (b) the adequate reporting of errors and complications in periodontology and dental implantology; and (c) efficacy trials vs effectiveness studies and their impact on the assessment and report of periodontal and implant treatment‐related risks and complications. [ABSTRACT FROM AUTHOR]

The assortment of periodontal and implant‐related treatments has been continuously improved over the last 50 years. Once the decision‐making process has been established and the treatment procedure applied, the partial or complete resolution of the problem (eg, periodontal probing depth reduction, clinical attachment level gain, gingival recession reduction, dental hypersensitivity decrease) and a diagnosis change with no or minimal occurrence of adverse events (ie, complications, harms, technical errors, or adverse/side effects) can be expected. The clear identification of the potential types of adverse effects, complications, or even errors is important for contemporary decision‐making processes, as they may be related to different local, systemic, and technical aspects. This chapter focused on four core components: (a) providing periodontal definitions for errors, complications, harms, and side effects; (b) defining the types of risk and the clinical impact of adverse effects, errors, and complications in periodontal and peri‐implant therapies; (c) evaluating the influence of accidental errors versus the lack of a proper treatment planning; and (d) reporting on the importance of establishing the "net benefit ratio" between the clinical improvements promoted by the therapy and the occurrence of potential adverse events. [ABSTRACT FROM AUTHOR]

Objective: To identify trends in complaints received by the Health and Disability Commissioner (HDC) about aged residential care (ARC) facilities in order to learn from and implement positive changes in care. Methods: A case study of 24 deidentified publicly available HDC cases across three large New Zealand ARC organisations was completed. Cross‐case analysis first involved analysis of each case individually and then compared all cases using inductive thematic analysis with the intention of drawing a single set of conclusions. Results: The speed at which the events occurred was contributory to the complaint, with 58% of the cases being rapid in nature and with sepsis being the predominant contributing factor to rapid decline and death. Six main diagnoses were indicators of deterioration: nutrition/hydration was indicated in 22% of the cases, followed by sepsis 17%, wounds 17%, UTI/renal issues 15%, falls 15% and respiratory issues 15%. Conclusions: Trends in Health and Disability complaints across multiple organisations can become a powerful tool for widespread quality improvement. This review highlights that the speed of deterioration triggered many complaints, especially in cases of sepsis which is possibly overlooked as a contributing problem. Also, that nutrition/hydration was indicated in many complaints and is an important condition‐indicator. Trends in complaints are not generalisable to all large organisations; however, they can be applied to individual facilities. [ABSTRACT FROM AUTHOR]

During the COVID‐19 pandemic, the structural biology community swung into action quickly and efficiently, and many urgent questions were solved by macromolecular structure determination. The Coronavirus Structural Task Force evaluated all structures from SARS‐CoV‐1 and SARS‐CoV‐2, but errors in measurement, data processing and modelling are present beyond these structures and throughout the structures deposited in the Protein Data Bank. Identifying them is only the first step; in order to minimize the impact that errors have in structural biology, error culture needs to change. It should be emphasized that the atomic model which is published is an interpretation of the measurement. Furthermore, risks should be minimized by addressing issues early and by investigating the source of a given problem, so that it may be avoided in the future. If we as a community can do this, it will greatly benefit experimental structural biologists as well as downstream users who are using structural models to deduce new biological and medical answers in the future. [ABSTRACT FROM AUTHOR]

Rationale, Aims, Objectives: Around one‐third of medication errors resulting in death within 48 h involve insulin therapy. Despite a growing number of interventional strategies that have been published over the past decade, it remains unclear which of these interventions is effective in reducing insulin errors. Therefore, the study aimed to synthesize interventions to reduce the frequency of insulin errors in either home or health care settings. Methods: This integrative review was conducted based on Whittemore and Knafl's four steps, which includes problem identification, literature search, data analysis and presentation. Six databases including Cumulative Index of Nursing and Allied Health Literature (CINAHL), Medline, PubMed, Scopus, PsychInfo and Cochrane were searched from January 2010 through July 2021. The level of evidence quality was assessed according to the Johns Hopkins Nursing Evidence‐Based Practice grading scale. Results: Sixteen studies meeting inclusion criteria were reviewed. The results provide strong support for teaching patients how to use automated bolus calculators and educating patients to self‐administer insulin to prevent insulin errors in the home setting. Computerized protocols, education and double‐checking procedures were also found to be effective strategies for minimizing insulin errors in healthcare settings. Conclusion: While the strategies might be effective in reducing insulin administration errors in the home settings, computerized protocols, continuing education and the manual validation of insulin products appear to be the most effective strategies for reducing such insulin errors in healthcare settings. Understanding these findings may help clinicians and patients to decrease the number of insulin errors administration. [ABSTRACT FROM AUTHOR]

The call for transparency with regards to the disclosure of errors in forensic science has permeated dialogues within the field, the legal arena and the public domain. While the challenges of meeting this need have been debated, no consistently accepted approach to recording or disclosing critical issues in forensic science has been developed. Part of the solution may lie in the quality system structures already present in forensic service providers world‐wide. However, while quality systems themselves may be standardized, the language used within them is not. We argue that the development of a common language for quality issues in forensic science may provide the key to unlocking this crucial information to support collaboration, continuous improvement, and the fundamental understanding of "error" in forensic science. This article is categorized under:Forensic Chemistry and Trace Evidence > Trace EvidenceJurisprudence and Regulatory Oversight > Communication Across Science and LawJurisprudence and Regulatory Oversight > Interdisciplinary CollaborationForensic Chemistry and Trace Evidence > Presentation and Evaluation of Forensic Science Output [ABSTRACT FROM AUTHOR]

A new family of compact schemes of increased accuracy using quasi‐variable mesh is presented for determining approximate solutions to the three‐space dimensions mildly nonlinear convection dominated diffusion equations. The main thought behind the proposed scheme is to get uniformly distributed local truncation error, which otherwise not possible in case of finite‐difference discretization using constant step‐sizes mesh points. According to the zero or nonzero values of mesh stretching quantities, the increased accuracy fourth‐order method refers to uniform meshes or quasi‐variable meshes schemes. It is easy to tune the mesh points depending upon the location of subdomains having comparatively more fluctuating solution behavior. The block‐tridiagonal construction of the Jacobian (iteration matrix) acquired with the new difference scheme makes it easier to implement with a reasonable computing time. We will describe the matrix and graph theoretic approach to analyze the convergence property and error estimate of the generalized scheme. A measure of accuracy, such as maximum errors, root‐mean‐squared errors, and numerical convergence rate, is examined by solving various forms of convection‐dominated diffusion equations. [ABSTRACT FROM AUTHOR]

Background: Alcohol intoxication impairs inhibitory control, resulting in disinhibited, impulsive behavior. The anterior cingulate cortex (ACC) plays an essential role in a range of executive functions and is sensitive to the effects of alcohol, which contributes to the top‐down cognitive dysregulation. This study used a multimodal approach to examine the acute effects of alcohol on the neural underpinnings of inhibitory control, inhibition failures, and neurobehavioral optimization as reflected in trial‐to‐trial dynamics of post‐error adjustments. Methods: Adult social drinkers served as their own controls by participating in the Go/NoGo task during acute alcohol and placebo conditions in a multi‐session, counterbalanced design. Distributed source modeling of the magnetoencephalographic signal was combined with structural magnetic resonance imaging to characterize the spatio‐temporal dynamics of inhibitory control in the time‐frequency domain. Results: Successful response inhibition (NoGo) elicited right‐lateralized event‐related theta power (4 to 7 Hz). Errors elicited a short‐latency increase in theta power in the dorsal (dACC), followed by activity in the rostral (rACC), which may underlie an affective "oh, no!" orienting response to errors. Error‐related theta in the dACC was associated with subsequent activity of the motor areas on the first post‐error trial, suggesting the occurrence of post‐error output adjustments. Importantly, a gradual increase of the dACC theta across post‐error trials closely tracked improvements in accuracy under placebo, which may reflect cognitive control engagement to optimize response accuracy. In contrast, alcohol increased NoGo commission errors, dysregulated theta during correct NoGo withholding, and abolished the post‐error theta enhancement of cognitive control. Conclusions: Confirming the sensitivity of frontal theta to inhibitory control and error monitoring, the results support functional and temporal dissociation along the dorso‐rostral axis of the ACC and the deleterious effects of alcohol on the frontal circuitry subserving top‐down regulation. Over time, alcohol‐induced disinhibition may give rise to compulsive drinking and contribute to alcohol misuse. [ABSTRACT FROM AUTHOR]

Patients with intellectual disabilities often fail to follow traditional tongue position instructions for panoramic radiographs resulting in missed pathology or unnecessary further radiation. This simple breathing technique is a new clinical instruction method for panoramic radiography developed to reduce the most common patient position error: patient failure to hold the tongue to the roof of the mouth. The technique is suitable for all patients including young patients and those with intellectual disabilities. The simple breathing technique uses 'tell‐show‐do' communication methods and does not mention the tongue but utilises the known tongue positions that occur during breathing and swallowing. This simple breathing technique instruction for panoramic radiography uses a demonstration of 'breathe‐in, breathe‐out, swallow, lips closed and hold still' to reduce the intensity of both the palatoglossal and pharyngeal airspaces on panoramic radiographs. This method, referred in this article as the simple breathing technique, can improve the diagnostic potential of panoramic radiographs and can be used with young children and patients with intellectual disabilities, and this slow breathing technique can help them further relax. [ABSTRACT FROM AUTHOR]

Background and Purpose: FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL‐FIRST) is a widely used and well‐validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL‐FIRST's algorithm is based on shape models derived from non‐MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL‐FIRST on MRIs from people with multiple sclerosis (PwMS). Methods: FSL‐FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated. Results: In the entire quantitative volumetric group, the mean volumetric error of FSL‐FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ2 = 18.14, p <.01 and χ2 = 64.89, p <.001, respectively). Finally, thalamus volume error was negatively associated with degree of atrophy, such that smaller thalami were systematically overestimated (r = –.28, p <.001). Conclusions: In PwMS, FSL‐FIRST thalamic segmentation miscalculates thalamic volumetry in a predictable fashion, and may be biased to overestimate highly atrophic thalami. As such, it is recommended that segmentations be reviewed and corrected manually when appropriate for specific studies. [ABSTRACT FROM AUTHOR]

The Royal College of Radiologists (RCR) is based in the United Kingdom but is a global organisation with members and fellows worldwide. In this invited article, the chair of the RCR Radiology Events and Learning (REAL) panel recounts his experience in looking at radiological errors. He starts with his personal work auditing his own mistakes as a junior consultant, describes what he learned in his departmental role in a large teaching hospital running a Radiology Events and Learning Meeting (REALM) and gives an overview of some of the work done over the last two decades by the RCR. This includes publishing national guidelines which set standards for running a REALM, setting up the REAL panel which produces a quarterly newsletter of cases from RCR members, and running an annual conference to share information with local radiology departments around the country. A review of the literature describing the drivers for this work and looking at the parallels with industry lies alongside the practical tips he found useful which he hopes would be helpful to anyone setting up their own departmental errors or discrepancy meeting. [ABSTRACT FROM AUTHOR]

Errors in diagnostic radiology are not infrequent. Patient harm related to these errors is however less common and may be avoided via various preventative mechanisms within the medical system including, but not limited to, multidisciplinary meetings, second opinions, subspecialty expertise and clinician experience. Failure at a number of points in the system is often required to result in patient harm. Radiologists, and in particular departmental leaders, should proactively address the known underlying root causes of diagnostic errors and cognitive biases, ensure systems are in place to promptly discover and control unmitigated root causes as they arise and ensure an unbiased 'blameless' or 'just' culture of error investigation and proces sing including the implementation of non‐punitive peer feedback and peer learning. This article provides an overview of errors in diagnostic radiology including the causes and potential ramifications and how we might reduce their frequency and impact. [ABSTRACT FROM AUTHOR]

Purpose: Calculating the adequate target margin for real‐time tumor tracking using the Cyberknife system is a challenging issue since different sources of error exist. In this study, the clinical log data of the Cyberknife system were analyzed to adequately quantify the planned target volume (PTV) margins of tumors located in the lung and abdomen regions. Methods: In this study, 45 patients treated with the Cyberknife module were examined. In this context, adequate PTV margins were estimated based on the Van Herk formulation and the uncertainty estimation method by considering the impact of errors and uncertainties. To investigate the impact of errors and uncertainties on the estimated PTV margins, a statistical analysis was also performed. Results: Our study demonstrates five different sources of errors, including segmentation, deformation, correlation, prediction, and targeting errors, which were identified as the main sources of error in the Cyberknife system. Furthermore, the clinical evaluation of the current study reveals that the two different formalisms provided almost identical PTV margin estimates. Additionally, 4–5 mm and 5 mm margins on average could provide adequate PTV margins at lung and abdomen tumors in all three directions, respectively. Overall, it was found that concerning the PTV margins, the impact of correlation and prediction errors is very high, while the impact of robotics error is low. Conclusions: The current study can address two limitations in previous researches, namely insufficient sample sites and a smaller number of patients. A comparison of the present results concerning the lung and abdomen areas with other studies reveals that the proposed strategy could provide a better reference in selection the PTV margins. To our knowledge, this study is one of the first attempts to estimate the PTV margins in the lung and abdomen regions for a large cohort of patients treated using the Cyberknife system. [ABSTRACT FROM AUTHOR]

Specimen management is a complex process that involves multiple steps and numerous health care personnel. Preventable specimen‐related errors are common and can occur during any phase of the specimen management process. Perioperative nurses manage specimens during the preanalytical phase before specimens are delivered to the laboratory for analysis. Errors in the preanalytical phase may include mislabeling, miscommunication, loss of a specimen, improper fixation of the specimen, and transport failures. The AORN "Guideline for specimen management" provides guidance for managing specimens collected during surgical and other invasive procedures, including recommendations for handling specific types of specimens. This article discusses the guideline recommendations for intraoperative team communication, transfer from the sterile field, containment, transport, and quality. A scenario describes a facility team's use of a root cause analysis and a failure modes and effects analysis tool to assess the risk and effects of specimen errors and create a process improvement plan. [ABSTRACT FROM AUTHOR]

A correction to the article "Socioeconomic status and infant nighttime sleep across the second year of life: The moderating role of infant attachment security" in the 2022 issue, volume 93, is presented which discusses errors related to variables in "Table 2 continued."

We examine the impact of human errors by front‐line supply chain employees on delivery delays. We build on normal accident theory (NAT), a multilevel theory describing the relationship between a firm's latent conditions (systemic managerial, technology, and social factors) and human errors. Latent conditions can have the unintended consequence of intensifying the impact of a human error, thus, we hypothesize a moderating effect of latent conditions on the relationship between errors and delivery delays. Hypotheses are tested using archival shipment data provided by a Fortune 500 company and archival carrier violations data. A multilevel design, with 299,399 shipments (level 1) nested within 97 carriers (level 2), was tested using mixed effects regression modeling. The results indicated that both dispatcher and driver errors were related to the probability of a late delivery, and that dispatcher errors were associated with longer delays. The moderating effects of several carrier latent conditions were significant and positive, indicating that both types of errors were more strongly associated with the likelihood of late delivery and that dispatcher errors were associated with longer delays when moderated by carrier latent conditions. The results are discussed from the perspective of NAT and technology management, developing prescriptions, and suggesting opportunities for future research. [ABSTRACT FROM AUTHOR]

What is the role of errors in infants' acquisition of basic skills such as walking, skills that require immense amounts of practice to become flexible and generative? Do infants change their behaviors based on negative feedback from errors, as suggested by "reinforcement learning" in artificial intelligence, or do errors go largely unmarked so that learning relies on positive feedback? We used falling as a model system to examine the impact of errors in infant development. We examined fall severity based on parent reports of prior falls and videos of 563 falls incurred by 138 13‐ to 19‐month‐old infants during free play in a laboratory playroom. Parent reports of notable falls were limited to 33% of infants and medical attention was limited to 2% of infants. Video‐recorded falls were typically low‐impact events. After falling during free play in the laboratory, infants rarely fussed (4% of falls), caregivers rarely showed concern (8% of falls), and infants were back at play within seconds. Impact forces were mitigated by infants' effective reactive behaviors, quick arrest of the fall before torso or head impact, and small body size. Moreover, falling did not alter infants' subsequent behavior. Infants were not deterred from locomotion or from interacting with the objects and elevations implicated in their falls. We propose that a system that discounts the impact of errors in early stages of development encourages infants to practice basic skills such as walking to the point of mastery. [ABSTRACT FROM AUTHOR]

Climate predictions using coupled models in different time scales, from intraseasonal to decadal, are usually affected by initial shocks, drifts, and biases, which reduce the prediction skill. These arise from inconsistencies between different components of the coupled models and from the tendency of the model state to evolve from the prescribed initial conditions toward its own climatology over the course of the prediction. Aiming to provide tools and further insight into the mechanisms responsible for initial shocks, drifts, and biases, this paper presents a novel data set developed within the Long Range Forecast Transient Intercomparison Project, LRFTIP. This data set has been constructed by averaging hindcasts over available prediction years and ensemble members to form a hindcast climatology, that is a function of spatial variables and lead time, and thus results in a useful tool for characterizing and assessing the evolution of errors as well as the physical mechanisms responsible for them. A discussion on such errors at the different time scales is provided along with plausible ways forward in the field of climate predictions. Plain Language Summary: The prediction of climate from weeks to years is usually made using complex numerical models that need to have an appropriate representation of the different components of the climate system (atmosphere, oceans, land areas, etc.,) as well as of their interactions. Most of these simulations, however, are affected by errors that originate in part from the numerical methods and approximations used to solve the system of equations of the atmospheric and oceanic systems, and in part by an incorrect representation of the interaction between components. Naturally, these errors lead to a significant decrease in the skill of the predictions, and therefore, must be taken into account. This study presents a new data set made from climate model predictions that have been manipulated in order to be useful for the assessment and further understanding of the physical mechanisms behind the aforementioned errors. The expected increase in our knowledge in the field will help us obtain more skillful climate predictions in the future. Key Points: Initial shocks, drifts, and biases affect climate predictions at all time scalesAs they usually lead to a substantial reduction of the prediction skill, further efforts toward their understanding are neededThe newly developed data set presented in this article is expected to serve as a useful tool for their study [ABSTRACT FROM AUTHOR]

The theoretical error rates in deterministic ion implantation when using an ion beam governed by a Poisson point process with a detector that counts the impacts are investigated. It is concluded that if the error rates are small, then for spots with nominally one implanted ion the probability of failure to implant the correct number is ≈κ/λ+η¯+λ/2 for a synchronous (i.e., pulsed) system or K/L+η¯+Lts for an asynchronous (i.e., continuous beam) system, where η¯ is the probability that the detector misses an ion impact, and L(K) and λ(κ) are the number of ions (dark counts) per unit time and per pulse, respectively. ts is the system reaction time for an asynchronous system. This approximation allows easy identification of the greatest need for engineering effort. Some experimental efforts to measure these parameters and their uncertainties are examined. [ABSTRACT FROM AUTHOR]

Time difference of arrival‐based localisation method has been extensively used by researchers for the partial discharge (PD) diagnosis despite being time‐inefficient and sensitive to time delay estimation. Most of the contemporary work focuses on overcoming these problems by using data‐driven approaches and/or statistical simulation methods. When used simultaneously, statistical simulation‐based methods facilitate the data‐driven approaches in terms of providing them with large amounts of data during the testing phase. However, the present work introduces a novel training phase strategy for a multi‐deep neural network model (MDNNM). In this method, 'N' number of randomly generated PD sources in 3‐D space are obtained statistically through virtual measurement method (VMM). Time delays amongst sensors, for the received ultra‐high frequency signals from these 'N' PDs, are used in training of the MDNNM. This enhances the model's PD detection ability, as the obtained time delays realise the measurement error beforehand; and consequently, the model learns to predict the PD coordinates accurately. After applying this MDNNM trained with a novel VMM practically, the experimental results show that a location accuracy of 1° can be obtained for a system error value of time difference up to 10 ns. [ABSTRACT FROM AUTHOR]

Relatively little is known about the relation between subthreshold error corrections and post‐error behavioral compensations. The present study utilized lateralized beta power, which has been shown to index response preparation, to examine subthreshold error corrections in a task known to produce response conflict, the Simon task. We found that even when an overt correction is not made, greater activation of the corrective response, indexed by beta suppression ipsilateral to the initial responding hand, predicted post‐error speeding, and enhanced post‐error accuracy at the single‐trial level. This provides support for the notion that response conflict associated with errors can be adaptive, and suggests that subthreshold corrections should be taken into account to fully understand error‐monitoring processes. Furthermore, we expand on previous findings that demonstrate that post‐error slowing and post‐error accuracy can be dissociated, as well as findings that suggest that frontal midline theta oscillations and the error‐related negativity (ERN) are dissociable neurocognitive processes. Impact Statement: A lack of consensus on whether error‐monitoring processes facilitate adaptive post‐error behavior might be attributable to the possibility that most investigations do not consider subthreshold error corrections. Here, we provide evidence—using a novel neural index—that even in the absence of an overt correction, subthreshold error corrections are adaptive. [ABSTRACT FROM AUTHOR]

Children's naive theories include misconceptions which can interfere with science learning. This research examined the effect of pairing anomalies with alternative theories, and their order of presentation, on children's belief revision. Children believe that heavy objects sink and light ones float. In a pre‐, mid‐, and post‐test design, 5‐year‐olds (N = 96) were assigned to one of two conditions, where they were either exposed to an alternative theory about buoyancy and then observed anomalies (Explanation‐First), or the reverse (Anomalies‐First). At mid‐test, children were more likely to revise their beliefs after exposure to an alternative theory than anomalies alone. At post‐test, children revised their naïve belief when they had access to an alternative theory before the anomalous evidence than in the opposite order. [ABSTRACT FROM AUTHOR]

But wood is not such a material, and for materials showing two or more degradation pathways, time-resolved changes in the effective heat of combustion need to be taken into account, before attributing characteristics of HRR curve peaks solely to thermal boundary condition effects. If one puts in a piece of wood into an oxygen-bomb calorimeter, values of the gross heat of combustion[2] of around 19.2-21.8 MJ kg SP -1 sp are found, with the net heat of combustion being around 17.8-20.4 MJ kg SP -1 sp . Keywords: errors; heat of combustion; heat release rate EN errors heat of combustion heat release rate 733 734 2 08/03/23 20230801 NES 230801 It has been well known for some decades that burning wood specimens show a heat release rate (HRR) curve with a peak at the start, a second peak near the end, and more or less a plateau in the middle. [Extracted from the article]

Typically, we think that blameworthiness is tied to normative failure. To be susceptible to blame for an act, attitude, or trait it must be that this target of blame entailed some sort of mistake: bad, wrong, or unjustified action on the part of the agent. In this paper, I challenge this common presumption. Instead, I suggest that blameworthiness needn't be a result of normative failure or a failure to maintain normative justification, but can also be a result of failures to conform to the standards that govern particular practices in which one is engaged, whether or not engagement in that practice, or indeed the norms that structure it, help to determine how one ought to live. [ABSTRACT FROM AUTHOR]

The diagnostics of Desroziers et al. have been used to estimate the uncertainties of Global Navigation Satellite System Radio Occultation (GNSS‐RO) observations. Compared with the uncertainties that are currently operational, the new uncertainties are smaller and vary with height, latitude, satellite identifier, and other variables. The initial tests allowed the observation uncertainties to vary with latitude, satellite identifier, and the tangent‐point height of the observation. Using these uncertainties for a winter period demonstrated clear improvements in the weather forecast skill. Further tests showed that this improvement derived from the variation of the uncertainties with satellite identifier and from using a smooth variation with latitude—the current method gives a sharp change in the uncertainty at 30° intervals in latitude. The diagnosis method indicated a maximum in the observation uncertainty just above the tropical tropopause (around 20 km). Experiments demonstrated that the high values for the observation uncertainty in this region degrade the forecast performance. It is suggested that this is a sign that this method is identifying some model errors incorrectly as observation errors, which may be a consequence of the known assumptions of the method being violated. The uncertainties diagnosed in this study were calculated over a one‐month period in winter 2017/2018, and the initial tests were conducted using a three‐month period for the same winter. Using uncertainties that vary with latitude, height, and satellite identifier in an experiment for summer 2018 resulted in a much smaller increase in forecast skill than for the winter period. Therefore uncertainties were diagnosed that vary with quantities other than latitude. The most effective of these is to allow the observation uncertainties to vary with the average temperature between the Earth's surface and 20 km. Uncertainties that vary with this and with satellite identifier and height give good forecast skill improvements in both seasons. [ABSTRACT FROM AUTHOR]

With state‐of‐the‐art plasma edge codes, which consist of coupled finite‐volume (FV) Monte Carlo (MC) codes, it is challenging to obtain accurate results for time‐dependent simulations in a feasible computational time. For steady‐state simulations, it has been recently demonstrated that the speed and accuracy can be drastically improved by choosing more suitable numerical parameters and including post‐processing averaging. This article extends the methodology for accuracy assessment to time‐dependent simulations. For a simplified one‐dimensional (1D) plasma edge model, we compare the numerical accuracy of solutions obtained with an implicit approach, where the code system is fully solved in each time step, to those with a mixed implicit/explicit approach, where only the FV code is converged in each time step. We demonstrate the importance of choosing the numerical parameters adequately in both approaches. [ABSTRACT FROM AUTHOR]

Background: During systematic reviews, "data abstraction" refers to the process of collecting data from reports of studies. The data abstractors' level of experience may affect the accuracy of data abstracted. Using data from a randomized crossover trial in which different data abstraction approaches were compared, we examined the association between abstractors' level of experience and accuracy of data abstraction. Methods: We classified abstractors as "more experienced" if they had authored three or more published systematic reviews, and "less experienced" otherwise. Each abstractor abstracted data related to study design, baseline characteristics, and outcomes/results from six articles. We considered two types of errors: incorrect abstraction and errors of omission. We estimated the proportion of errors by level of experience using a binomial generalized linear mixed model. Results: We used data from 25 less experienced and 25 more experienced data abstractors. Overall error proportions were similar for less experienced abstractors (21%) and more experienced abstractors (19%). Compared with less experienced abstractors, more experienced abstractors had a lower odds of errors for data items related to outcomes/results (adjusted odds ratio [OR] = 0.53; 95% CI, 0.34‐0.82) and potentially for data items related to study design (adjusted OR = 0.83; 95% CI, 0.64‐1.09) but a potentially higher odds of errors for items related to baseline characteristics (adjusted OR = 1.42; 95% CI, 0.97‐2.06). Conclusion: Experience of data abstraction matters little. Errors are reduced by adjudication but still remain high for data items related to outcomes/results. [ABSTRACT FROM AUTHOR]

Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demonstrated enhanced anterior cingulate cortex activity for errors that were later corrected versus repeated errors even when a substantial delay between the error and the opportunity to correct was introduced. We aimed at identifying the electrophysiological correlates of these processes by investigating the feedback‐related negativity (FRN) and stimulus‐locked P3. Participants had to learn and recall the location of 2‐digit targets over consecutive rounds. Feedback was provided in two steps, first a color change indicated a correct or incorrect response (feedback phase) followed by presentation of the correct digit information (re‐encoding phase). Behaviorally, participants improved performance from the first to the third round. FRN amplitudes time‐locked to feedback were enhanced for corrected compared to repeated errors. The P3 in response to re‐encoding did not differ between the two error types. The finding that FRN amplitudes positively predicted memory performance is consistent with the idea that the FRN reflects prediction errors and the need for enhanced cognitive control. Interestingly, this happens early during feedback processing and not at a later time point when re‐encoding of correct information takes place. The prediction error signal reflected in the FRN is usually elicited by performance errors, but may thus also play a role in preparing/optimizing the system for memory formation. This supports the existence of a close link between action control and memory processes even when there is a substantial delay between error feedback and the opportunity to correct the error. [ABSTRACT FROM AUTHOR]

The question of whether individual judgment errors survive in market equilibrium is an issue that naturally lends itself to experimental analysis. Here, the Monty Hall problem is used to detect probability judgment errors both in a cohort of individuals and in a market setting. When all subjects in a cohort made probability judgment errors, market prices also reflected the error. However, competition among two bias-free subjects was sufficient to drive prices to error-free levels. Thus, heterogeneity in behavior can be an important factor in asset pricing, and further, it may take few bias-free traders to make asset prices bias-free. [ABSTRACT FROM AUTHOR]

To improve audit effectiveness, public accounting firms have organized their practices to include hierarchical review by teams organized along industry lines. We examine how industry specialized auditor teams detect errors, using a sophisticated experimental design. Our analysis of nominal teams created from seniors and managers working individually shows that seniors add value to the team by detecting more mechanical errors while managers detect more conceptual errors. Working within specialization, managers and seniors both contribute in a nonredundant way to the team's overall effectiveness. We also find that the nominal teams outperform real teams in the detection of mechanical but not conceptual errors. These results only hold when the auditors work within in their industry specialization. Out of specialization the auditors are not effective at detecting errors, and real teams perform below the nominal team benchmark in the detection of both mechanical and conceptual errors. [ABSTRACT FROM AUTHOR]

This study examines analyst forecast errors within the context of stock recommendations. We predict positive forecast error (i.e., optimism) for buy recommendations and negative forecast error (i.e., pessimism) for sell recommendations. We offer two explanations for this prediction: (1) the unconscious tendency to process information in a manner that supports one's goal, which we refer to as the "objectivity illusion" hypothesis, and (2) the economic incentive to boost trade, which we refer to as the "trade boosting" hypothesis. The pattern of analyst forecast bias we predict (i.e., optimism for buys and pessimism for sells) is opposite in direction to that predicted by the management relations hypothesis—a commonly cited hypothesis for analyst forecast bias. We find broker-analyst earnings forecast errors are significantly optimistic for buy recommendations and significantly pessimistic for sell recommendations, consistent with the objectivity illusion and trade boosting hypotheses. Our study indicates that the pattern of results reported in prior research (i.e., increasingly optimistic earnings forecasts as the stock recommendation becomes less favorable) is likely driven by a correlated omitted variable, actual earnings. Results of an analysis to distinguish between trade boosting and objectivity illusion appear more consistent with the objectivity illusion. [ABSTRACT FROM AUTHOR]

This paper examines underwriters' pricing errors and the information content of first-day trading activity in IPOs. We show that first-day winners continue to be winners over the first year, and first-day dogs continue to be relative dogs. Exceptions are "extra-hot" IPOs, which provide the worst future performance. We also demonstrate that large, supposedly informed, traders "flip" IPOs that perform the worst in the future. IPOs with low flipping generate abnormal returns of 1.5 percentage points per month over the first six months beginning on the third day. We show that flipping is predictable and conclude that underwriters' pricing errors are intentional. [ABSTRACT FROM AUTHOR]

Estimations that include numerical information are ubiquitous in our daily lives, for example, housing prices, calories, etc. In the present work, we investigate how the type of information used in an estimate, particularly its level of imprecision, influences evaluations of source trustworthiness after the target value of the estimate is revealed. Specifically, building upon prior work suggesting that (a) imprecise estimates are perceived to be less accurate than precise estimates and (b) performing below expectations results in negative source evaluations, we hypothesize that if the estimate is revealed to be incorrect, imprecise estimates (i.e., 400) elicit higher source trustworthiness than precise estimates (i.e., 417), even if the imprecise estimate is objectively more incorrect (i.e., target value: 570). In addition, we find that this effect also influences consumers' loyalty toward the source of the estimate. Four studies and a single‐paper meta‐analysis offer triangulating evidence for this prediction and its underlying psychological mechanism. Overall, this work contributes to research on estimates, source evaluations, numerical information, and the influence of errors on consumer behavior. [ABSTRACT FROM AUTHOR]

Satellite scatterometers provide the only regular observations of surface wind vectors over vast swaths of the world oceans, including coastal regions, which are of great scientific and societal interest but still present challenges for remote sensing. Here we demonstrate systematic scatterometer wind errors near Hawaii's Big Island: Two counter‐rotating lee vortices, which are clear in the International Comprehensive Ocean‐Atmosphere Data Set ship‐based wind climatology and in aircraft observations, are absent in the Jet Propulsion Laboratory and Remote Sensing Systems scatterometer wind climatologies. We demonstrate similar errors in the representation of transient Catalina Eddy events in the Southern California Bight. These errors likely arise from the nonuniqueness of scatterometer wind observations, that is, an "ambiguity removal" is required during processing to select from multiple wind solutions to the geophysical model function. We discuss strategies to improve the ambiguity selection near coastal mountains, where small‐scale wind reversals are common. Key Points: Orographic wind features near Hawaii's Big Island and southern California are absent in satellite scatterometer wind observationsThese systematic scatterometer wind errors near coastal mountains are due at least partially to ambiguity removal errorsPrior studies based on scatterometer winds therefore likely underestimate the influence of coastal mountains on coastal ocean circulation [ABSTRACT FROM AUTHOR]