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This study explores the capabilities of large language models to replicate the behavior of individuals with underdeveloped cognitive and language skills. Specifically, we investigate whether these models can simulate child-like language and cognitive development while solving false-belief tasks, namely, change-of-location and unexpected-content tasks. GPT-3.5-turbo and GPT-4 models by OpenAI were prompted to simulate children (N = 1296) aged one to six years. This simulation was instantiated through three types of prompts: plain zero-shot, chain-of-thoughts, and primed-by-corpus. We evaluated the correctness of responses to assess the models' capacity to mimic the cognitive skills of the simulated children. Both models displayed a pattern of increasing correctness in their responses and rising language complexity. That is in correspondence with a gradual enhancement in linguistic and cognitive abilities during child development, which is described in the vast body of research literature on child development. GPT-4 generally exhibited a closer alignment with the developmental curve observed in 'real' children. However, it displayed hyper-accuracy under certain conditions, notably in the primed-by-corpus prompt type. Task type, prompt type, and the choice of language model influenced developmental patterns, while temperature and the gender of the simulated parent and child did not consistently impact results. We conducted analyses of linguistic complexity, examining utterance length and Kolmogorov complexity. These analyses revealed a gradual increase in linguistic complexity corresponding to the age of the simulated children, regardless of other variables. These findings show that the language models are capable of downplaying their abilities to achieve a faithful simulation of prompted personas., Competing Interests: NO., (Copyright: © 2024 Milička et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The popularity and rapid spread of new psychoactive substances is why there is an urgent need for their fast monitoring in saliva in the field with electrodes modified with a selective receptor. Oligomers of electrochemically oxidized 3-aminobenzoic acid that are deposited on the surface of a graphite screen-printed electrode (o-3ABA/G/SPE) is proposed as a selector for the analyte of forensic interest. The oligomeric structure and existence of the zwitterionic form of o-3ABA on the G/SPE surface was confirmed using scanning electron microscopy, Raman spectroscopy and cyclic voltammetry techniques. The equilibrium adsorption constants between o-3ABA and 2-aminoindane (primary amine: K ads (2-AI) = 5.31 × 10 4 ) and selected synthetic cathinones (secondary amine: K ads (butylone) = 6.12 × 10 5 , tertiary amines: K ads (MDPV) = 3.41 × 10 4 and K ads (naphyrone) = 1.01 × 10 4 ) were estimated using the electrochemical impedance spectroscopy (EIS) technique. The EIS technique was applied for determining a 1.0 μM concentration of 2-AI (RSD 3.5-4.0%) and butylone (RSD 4.9-6.4%) in the model and oral fluid samples.