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This document provides guidance on the use of artificial intelligence (AI), natural language processing (NLP), and language models (LLMs) in scholarly publishing. It emphasizes the importance of transparency, responsibility, and accountability in the use of AI to ensure the integrity and quality of published research. Authors are advised to disclose their use of AI tools and provide detailed information about their usage. Peer reviewers are cautioned against using AI tools that may compromise confidentiality, and editors are responsible for effectively and transparently implementing AI tools. Efforts should be made to bridge the digital divide and prevent disparities in access to AI technologies. Data protection measures, intellectual property rights, and addressing AI-induced academic misconduct are also highlighted as important considerations. [Extracted from the article]

Seepage is a typical hydraulic factor that can initiate the breaching process in a levee system. If not identified and treated on time, seepages can be a severe problem for levees, weakening the levee structure and eventually leading to collapse. Therefore, it is essential always to be vigilant with regular monitoring procedures to identify seepages throughout these levee systems and perform adequate repairs to limit potential threats from unforeseen levee failures. This paper introduces a fully convolutional neural network to identify and segment seepage from the image in levee systems. To the best of our knowledge, this is the first work in this domain. Applying deep learning techniques for semantic segmentation tasks in real-world scenarios has its own challenges, especially the difficulty for models to effectively learn from complex backgrounds while focusing on simpler objects of interest. This challenge is particularly evident in the task of detecting seepages in levee systems, where the fault is relatively simple compared to the complex and varied background. We addressed this problem by introducing negative images and a controlled transfer learning approach for semantic segmentation for accurate seepage segmentation in levee systems. [ABSTRACT FROM AUTHOR]

The article offers information on the 10th International Congress on Peer Review and Scientific Publication and its call for abstract submissions. Topics include the evolving challenges in scientific publication such as AI and reproducibility issues, the Congress's emphasis on novel, data-driven research to improve peer review, and its encouragement of interdisciplinary studies across diverse scientific fields.

The article focuses on the periodical's achievements and initiatives in 2023. It highlighting key metrics; new initiatives like JAMA Express for timely publication of high-importance manuscripts; the diverse range of content published to cater to global readership interests, including Alzheimer's research, COVID-19 studies and discussions on artificial intelligence in medicine; and fellowship programs and partnerships with academic institutions.

The African Journal Partnership Program has developed guidance on the use of artificial intelligence (AI) in scholarly publishing. The guidance emphasizes the responsible and ethical use of AI, highlighting the potential benefits and challenges it presents. It stresses the importance of access to AI technologies in low- and middle-income countries to prevent knowledge disparities. The guidance also addresses issues such as data protection, intellectual property, plagiarism, and ownership of AI-generated content. It provides recommendations for authors, peer reviewers, and editors to ensure the appropriate use of AI in research and publication. [Extracted from the article]

This article explores the use of artificial intelligence (AI) in scholarly publishing and the potential benefits and challenges it presents. While AI technologies like machine learning and natural language processing can streamline research and publishing, concerns about bias, inaccuracies, and ethical issues arise. The article emphasizes the need for guidance and best practices to ensure responsible use of AI in research and publication, addressing transparency, responsibility, and accountability. It also highlights the importance of addressing data privacy, authorship attribution, intellectual property rights, and plagiarism detection. Access to advanced AI technologies is not uniform worldwide, and ensuring access in scholarly publishing is crucial to prevent disparities in knowledge creation and dissemination. The article concludes by providing recommendations for authors on the use of AI tools in manuscript preparation, emphasizing transparency and accountability. [Extracted from the article]

An editorial is presented the recommendations made by the National Academies of Sciences, Engineering, and Medicine (NASEM) to shift away from using race, ethnicity, and geographic origin as proxies for genetic ancestry groups in genetic and genomic research, proposing a framework for behavior change in the field and emphasizing the need for sustained support from various stakeholders.

An editorial provides comprehensive guidance for authors, researchers, reviewers, and editors on the transparent and accountable reporting of artificial intelligence (AI) use in medical research and scholarly publication. It emphasizes the importance of clear documentation, adherence to reporting guidelines, and addressing potential biases and inaccuracies associated with AI models.

The article focuses on advancing equity within a medical publishing network, specifically discussing self-reported demographics of editors and editorial board members. Topics discussed include efforts to ensure diverse representation, the standardized schema for demographic reporting, and initiatives for improving equity and inclusion in medical publishing.

Background: There is increasing evidence for close interrelations between vestibular and emotional brain networks. A study in patients with bilateral peripheral vestibulopathy (BVP) showed relatively low vertigo-related anxiety (VRA), despite high physical impairment. The current working hypothesis proposes the integrity of the peripheral vestibular system as a prerequisite for development of VRA. Here we contribute by evaluating VRA and vestibular-related handicap in central vestibular disorders. Methods: Of 6396 patients presenting in a tertiary vertigo centre, 306 were identified with four clear central vestibular disorders: pure cerebellar ocular motor disorder (COD; 61), cerebellar ataxia (CA; 63), atypical parkinsonian syndromes (APS; 28), vestibular migraine (VM; 154). Their results of the Vertigo Handicap Questionnaire (VHQ), with its subscales for anxiety and handicapped activity, were compared to those of 65 BVP patients. Postural instability was measured on a force-plate. Multivariate linear regression was used to adjust for patient demographics. Results: Patients with chronic central vestibular disorders (COD, CA, APS) had relatively low VRA levels comparable to those in BVP, independent of increased handicapped activity or postural instability. Only VM patients showed significantly higher VRA, although their activity impairment and postural instability were lowest. No significant differences within chronic central vestibular disorders were found for VRA and subjective activity impairment. Conclusions: Subjective and objective vestibular-related impairment are not necessarily correlated with vestibular-related anxiety in central vestibular disorders. Our findings rather support the hypothesis that, in addition to an intact peripheral, an intact central vestibular system could also serve as a prerequisite to develop specific VRA. [ABSTRACT FROM AUTHOR]

Numerous variants of the basic deep segmentation model—U-Net—have emerged in recent years, achieving reliable performance across different benchmarks. In this paper, we propose an improved version of U-Net with higher performance and reduced complexity. This improvement was achieved by introducing a sparsely connected depth-wise separable block with multiscale filters, enabling the network to capture features of different scales. The use of depth-wise separable convolution significantly reduces the number of trainable parameters, making the training faster, while reducing the risk of overfitting. We used our developed sinkhole dataset and the available benchmark nuclei dataset to assess the proposed model's performance. Pixel-wise annotation is laborious and requires a great deal of human expertise; therefore, we propose a fully deep convolutional autoencoder network that utilizes the proposed block to automatically annotate the sinkhole dataset. Our segmentation model outperformed the state-of-the-art methods, including U-Net, Attention U-Net, Depth-Separable U-Net, and Inception U-Net, achieving an average improvement of 1.2% and 1.4%, respectively, on the sinkhole and the nuclei datasets, with 94% and 92% accuracy, as well as a reduced training time. It also achieved 83% and 80% intersection-over-union (IoU) on the two datasets, respectively, which is an 11.8% and 9.3% average improvement over the above-mentioned models. [ABSTRACT FROM AUTHOR]

Two studies investigated the effects of exposure to disinformation on citizens' evaluation of politicians and the impact of corrections. Study 1 tested the roles of message valence and relational closeness of social media connections sharing disinformation. Study 2 examined whether corrections on social networking sites could mitigate the influence of disinformation. Results of the first study indicate a limited persuasive effect of disinformation, with negative disinformation being more entertaining but potentially less credible than positive disinformation. Effects of corrections in Study 2 were strong. There was no consistent influence of whether disinformation was shared by a close versus distant friend. [ABSTRACT FROM AUTHOR]

An editorial is presented on the growing role of artificial intelligence (AI) in healthcare, emphasizing Journal of the American Medical Association (JAMA) commitment to promoting AI science that enhances patient care, improves clinical outcomes and addresses issues of equity in healthcare applications of AI. It mentions the importance of rigorous scientific development, evaluation, and implementation of AI technologies in healthcare, patient-centered care and health system quality improvement.

The article offers information on a framework for considering causal inference from observational studies published in medical journals, including JAMA. Topics include the rationale for the framework, its application in specific study designs, and how it could be implemented by authors, peer reviewers, and editors. The framework aims to ensure that findings from observational designs are appropriately interpreted and applied to improve patient care and public health.

Online information repositories increasingly serve as memory aids in people's lives. Access to such information stores, however, can result in false perceived equivalencies between web-based information and personal knowledge, which can in turn influence judgments of oneself, of information search tasks, and of the Internet itself. Cognitive processing fluency, access to reliable web-based information, and actively searching for information are shown in a series of experiments to be associated with judgments related to metacognition and task performance. In the context of online information repositories accessed via web search activities, people are shown to (a) overemphasize the degree to which they find the web to be a ready source of relevant information, (b) overestimate their future task performance and the ease of tasks, and (c) inflate their own perceived cognitive and memory abilities. Results also show that those who are least competent in task completion overestimate their relative performance, whereas the most competent underestimate theirs, and that the availability of web-based information can inflate people's estimated performance, particularly among the more competent. Collectively, three interrelated studies add considerable new insight regarding the impacts of near-ubiquitous access to contemporary information-saturated environments. [ABSTRACT FROM AUTHOR]

Key points: Inclusive language will make scholarly publishing more accurate and more respectful, and it has the potential to help authors reach a wider audience.JAMA and the JAMA Network journals, the American Chemical Society and the Coalition for Diversity and Inclusion in Scholarly Communications have free guides on inclusive language, formatting and images.The guides provide principles and rationale, as well as examples of preferred language, in order to equip people with knowledge to choose the most inclusive words even as terminology preferences change. [ABSTRACT FROM AUTHOR]

Estimates of the duration of time intervals and other magnitudes exhibit characteristic biases that likely result from error minimization strategies. To investigate such phenomena, magnitude reproduction tasks are used with humans and other primates. However, such behavioral tasks do not exist for rodents, one of the most important animal orders for neuroscience. We, therefore, developed a time reproduction task that can be used with rodents. It involves an animal reproducing the duration of a timed visual stimulus by walking along a corridor. The task was implemented in virtual reality, which allowed us to ensure that the animals were actually estimating time. The hallway did not contain prominent spatial cues and movement could be de-correlated from optic flow, such that the animals could not learn a mapping between stimulus duration and covered distance. We tested the reproduction of durations of several seconds in three different stimulus ranges. The gerbils reproduced the durations with a precision similar to experiments on humans. Their time reproductions also exhibited the characteristic biases of magnitude estimation experiments. These results demonstrate that our behavioral paradigm provides a means to study time reproduction in rodents. [ABSTRACT FROM AUTHOR]

Background: Over the last decades, brain surgery became a more frequently applied treatment for temporal lobe epilepsy (TLE). Despite its success, several studies found de-novo post-operative psychiatric symptoms in TLE surgery patients. Cognitive behavioural therapy is effective to treat brain healthy psychiatric patients but might not be translatable to patients with resections in emotion regulating networks as these areas seem to be essentially involved in successful psychotherapeutic treatment. Methods: Here we report the case of a female patient with medically refractory medial temporal lobe epilepsy resulting in left anterior temporal lobectomy at age 35. Post operation she did not show adequate fearful response but at the same time manifested symptoms of a severe panic disorder. We investigated if this patient, despite lesions in emotion-behaviour brain circuits, can benefit from cognitive behavioural therapy. Results: The intervention, customized to the specific resources and difficulties of the patient, was effective in stopping panic attacks and improving social functioning. Conclusions: This case shows that MTL brain surgery patients may benefit from CBT and demonstrates the important and if yet still somewhat mysterious role of the amygdala in emotion regulation processes. [ABSTRACT FROM AUTHOR]

The article discusses the importance of inclusive language in medical and scientific publications when describing people. It emphasizes the need to avoid noninclusive language that may convey bias and instead use terminology that promotes clarity, inclusiveness, respect, and fairness. The article also mentions the draft guidance on reporting gender, sex, gender identity, sexual orientation, and age in medical and scientific publications, which provides recommendations for accurate and respectful language usage. The guidance is open for public review and comment until September 30, 2024, and will be revised and published in the AMA Manual of Style. [Extracted from the article]

Vestibular information is ubiquitous and often processed jointly with visual, somatosensory and proprioceptive information. Among the cortical brain regions associated with human vestibular processing, area OP2 in the parietal operculum has been proposed as vestibular core region. However, delineating responses uniquely to vestibular stimulation in this region using neuroimaging is challenging for several reasons: First, the parietal operculum is a cytoarchitectonically heterogeneous region responding to multisensory stimulation. Second, artificial vestibular stimulation evokes confounding somatosensory and nociceptive responses blurring responses contributing to vestibular perception. Furthermore, immediate effects of vestibular stimulation on the organization of functional networks have not been investigated in detail yet. Using high resolution neuroimaging in a task-based and functional connectivity approach, we compared two equally salient stimuli—unilateral galvanic vestibular (GVS) and galvanic nociceptive stimulation (GNS)—to disentangle the processing of both modalities in the parietal operculum and characterize their effects on functional network architecture. GNS and GVS gave joint responses in area OP1, 3, 4, and the anterior and middle insula, but not in area OP2. GVS gave stronger responses in the parietal operculum just adjacent to OP3 and OP4, whereas GNS evoked stronger responses in area OP1, 3 and 4. Our results underline the importance of considering this common pathway when interpreting vestibular neuroimaging experiments and underpin the role of area OP2 in central vestibular processing. Global network changes were found during GNS, but not during GVS. This lack of network reconfiguration despite the saliency of GVS may reflect the continuous processing of vestibular information in the awake human. [ABSTRACT FROM AUTHOR]

Chatbots, ChatGPT, and scholarly manuscripts: WAME recommendations on ChatGPT and chatbots in relation to scholarly publications. According to I Nature, i that article's inclusion of ChatGPT in the author byline was an "error that will soon be corrected."[6] However, these articles and their nonhuman "authors" have already been indexed in PubMed and Google Scholar. If these models or tools are used to create content or assist with writing or manuscript preparation, authors must take responsibility for the integrity of the content generated by these tools. Editorial Artificial intelligence (AI) technologies to help authors improve the preparation and quality of their manuscripts and published articles are rapidly increasing in number and sophistication. [Extracted from the article]

In spite of the capacity for the Internet to connect people and information irrespective of geography, physical location may paradoxically provide influential indicators of the perceived expertise of strangers and the credibility of the information they provide that may in turn guide people's behaviors. To address this, this study examined the novel concept of geospatial concordance or the degree to which entities implicated in the sharing of aggregated opinions in online information pools are physically close to each other in geographic space. Predictions were tested in the context of user-generated online reviews using stimuli reflecting various types of geospatial concordance: between information consumers and online reviewers, between reviewed venues and their reviewers, and between consumers and reviewed venues. Findings support geographic perspectives emphasizing space as a mental construction imbued with particular meaning and confirm psychological views that people mentally construe places at different levels of abstraction, depending on their psychological, and physical, distance from them. [ABSTRACT FROM AUTHOR]

The authors discuss the updated guidance of the "Journal of the American Medical Association" (JAMA) and JAMA Network journals on the reporting of race and ethnicity-related information in medical and science publications. Topics explored include the significance of proper use of terms when addressing race and ethnicity, the acknowledgment of controversies involving racism in medicine and disparities in health care, and the availability of the guidance on the JAMA website.

The article introduces JAMA Data Brief, a new department in JAMA's Medical News & Perspectives, focusing on data visualizations and stories that contextualize health, healthcare, and health policy data, with the inaugural brief addressing health misinformation during the COVID-19 pandemic.

The article discusses the JAMA Summit that was held in Chicago, U.S. in October 2023. Topics discussed include the challenges and opportunities to improve the design and conduct of randomized clinical trials, with a focus on making them more responsive to the needs in clinical practice. Attendees included researchers, funders, regulators, patient advocates, policymakers, innovators, and industry representatives.

The authors talks about the reporting of race and ethnicity in medical and science journals. Topics discussed include the "AMA Manual of Style: A Guide for Authors and Editors," guidance of the JAMA Network journals for reporting race/ethnicity and other demographic information in research articles in the instructions for authors, and geographic origin and regionalization considerations.

An editorial is presented the importance of health as a central policy issue in the 2024 US election and the need for rigorous research to inform health care and public health policies. Topics include various health-related challenges, such as health disparities, immigration policies, LGBTQ rights, firearm regulations, and the impact of the economy on mental health and access to essential needs.

Brain atlases and templates are core tools in scientific research with increasing importance also in clinical applications. Advances in neuroimaging now allowed us to expand the atlas domain to the vestibular and auditory organ, the inner ear. In this study, we present IE-Map, an in-vivo template and atlas of the human labyrinth derived from multi-modal high-resolution magnetic resonance imaging (MRI) data, in a fully non-invasive manner without any contrast agent or radiation. We reconstructed a common template from 126 inner ears (63 normal subjects) and annotated it with 94 established landmarks and semi-automatic segmentations of all relevant macroscopic vestibular and auditory substructures. We validated the atlas by comparing MRI templates to a novel CT/micro-CT atlas, which we reconstructed from 21 publicly available post-mortem images of the bony labyrinth. Templates in MRI and micro-CT have a high overlap, and several key anatomical measures of the bony labyrinth in IE-Map are in line with micro-CT literature of the inner ear. A quantitative substructural analysis based on the new template, revealed a correlation of labyrinth parameters with total intracranial volume. No effects of gender or laterality were found. We provide the validated templates, atlas segmentations, surface meshes and landmark annotations as open-access material, to provide neuroscience researchers and clinicians in neurology, neurosurgery, and otorhinolaryngology with a widely applicable tool for computational neuro-otology. [ABSTRACT FROM AUTHOR]

Research typically presumes that people believe misinformation and propagate it through their social networks. Yet, a wide range of motivations for sharing misinformation might impact its spread, as well as people's belief of it. By examining research on motivations for sharing news information generally, and misinformation specifically, we derive a range of motivations that broaden current understandings of the sharing of misinformation to include factors that may to some extent mitigate the presumed dangers of misinformation for society. To illustrate the utility of our viewpoint we report data from a preliminary study of people's dis/belief reactions to misinformation shared on social media using natural language processing. Analyses of over 2,5 million comments demonstrate that misinformation on social media is often disbelieved. These insights are leveraged to propose directions for future research that incorporate a more inclusive understanding of the various motivations and strategies for sharing misinformation socially in large-scale online networks. [ABSTRACT FROM AUTHOR]

The authors discuss a research of the benefits and challenges of using preprints for non-peer reviewed medical research reports. Topics discussed include the goals of preprints, aim of clinical medical research to improve patient outcomes and public health, hosting and archiving preprint manuscripts in preprint servers, analysis of the policies of preprint servers and review of content on the medRxiv preprint server and trends a year after it was launched in June 2019.

Purpose: Concerns about conflicts of interest (COIs) in research and health care are well known, but recent reports of authors failing to disclose potential COIs in journal articles threatens the integrity of the scholarly literature. While many nursing journals have published editorials on this topic, review of nursing journal policies on and experiences with COIs has not been reported. The purposes of this study were to examine the extent to which nursing journals have COI policies and require disclosures by authors, peer reviewers, editorial board members, and editors who have a role in journal content decisions. Design: This cohort study addressed top‐ranked nursing journal policies about and experiences with COIs in scholarly publications. Methods: An analysis of COI policies in the instructions for authors of 118 journals listed in the nursing category of Clarivate Analytics Journal Citation Reports was completed in 2019. An electronic survey of the editors was also conducted to determine their awareness and experience with COI policies for their journals. Characteristics of the journals and policies were assessed. Information on polices about COIs for editors and peer reviewers were also reviewed. A content analysis of the policies included assessment of best practices and gaps in requirements. Findings: For the journal policy assessment, 116 journals that publish only in the English language were eligible. The majority (n = 113; 97.4%) of journals had a statement on COI policies for authors, but only 42 (36.2%) had statements for peer reviewers and only 37 (31.9%) had statements for editors. A total of 117 journal editors were sent the survey. One declined to participate, leaving a total of 116 eligible editors; 82 (70.6%) responded and 34 did not respond. Sixty‐seven (81.7%) of the 82 editors indicated that their journal had a policy about COIs for authors. Seventy‐four editors (63.7%) responded to the question about their journal having a policy about COIs for peer reviewers and editors. Thirty‐three (44.5%) of the respondents indicated their journal had a COI policy for peer reviewers, and 29 (39.1%) stated they had a policy for editors. Few editors (n = 7; 9%) indicated that they had encountered problems pertaining to author COIs. Conclusions: Findings from this study may help promote ethical publication practices through comprehensive policies on disclosure and management of nursing journal authors, peer reviewers, and editors. Clinical Relevance: Declarations of potential conflicts of interest promote transparency and allows the consumer of research to take that into consideration when considering the findings of a study. [ABSTRACT FROM AUTHOR]

An experiment using a representative sample of US. Internet users in the context of online encyclopedias is conducted to understand how the type of information source (expert-generated, user-generated, or hybrid [both expert- and user-generated]) and message sidedness (one- versus two-sided) affect perceived information credibility. Additionally, individual differences in cognitive styles, including need for cognition and flexible thinking, are hypothesized to moderate these relationships. Results showed that expert-generated messages are regarded as most credible, whereas two-sided messages were only perceived as more credible than one-sided messages when originating from a hybrid source. Moreover, the effect of message sidedness is stronger among people with higher flexible thinking, but not among those with high need for cognition. This study extends knowledge of source type to include the diversity of possibilities available online today, clarifies how message sidedness and type of information source affect the perceived credibility of online information, and offers new insight into how individual psychological differences affect the evaluation of online information credibility, including the identification of flexible thinking as an important variable in this domain. Results of this study help to clarify how people navigate the wide diversity of information options available today in efforts to locate credible information to guide their attitudes and behaviors. [ABSTRACT FROM AUTHOR]