BACKGROUND: The rapid evolution of ChatGPT has generated substantial interest and led to extensive discussions in both public and academic domains, particularly in the context of medical education.
OBJECTIVE: This study aimed to evaluate ChatGPT\'s performance in a pulmonology examination through a comparative analysis with that of third-year medical students.
METHODS: In this cross-sectional study, we conducted a comparative analysis with 2 distinct groups. The first group comprised 244 third-year medical students who had previously taken our institution\'s 2020 pulmonology examination, which was conducted in French. The second group involved ChatGPT-3.5 in 2 separate sets of conversations: without contextualization (V1) and with contextualization (V2). In both V1 and V2, ChatGPT received the same set of questions administered to the students.
RESULTS: V1 demonstrated exceptional proficiency in radiology, microbiology, and thoracic surgery, surpassing the majority of medical students in these domains. However, it faced challenges in pathology, pharmacology, and clinical pneumology. In contrast, V2 consistently delivered more accurate responses across various question categories, regardless of the specialization. ChatGPT exhibited suboptimal performance in multiple choice questions compared to medical students. V2 excelled in responding to structured open-ended questions. Both ChatGPT conversations, particularly V2, outperformed students in addressing questions of low and intermediate difficulty. Interestingly, students showcased enhanced proficiency when confronted with highly challenging questions. V1 fell short of passing the examination. Conversely, V2 successfully achieved examination success, outperforming 139 (62.1%) medical students.
CONCLUSIONS: While ChatGPT has access to a comprehensive web-based data set, its performance closely mirrors that of an average medical student. Outcomes are influenced by question format, item complexity, and contextual nuances. The model faces challenges in medical contexts requiring information synthesis, advanced analytical aptitude, and clinical judgment, as well as in non-English language assessments and when confronted with data outside mainstream internet sources.

This paper examines how humans judge the capabilities of artificial intelligence (AI) to evaluate human attributes, specifically focusing on two key dimensions of human social evaluation: morality and competence. Furthermore, it investigates the impact of exposure to advanced Large Language Models on these perceptions. In three studies (combined N = 200), we tested the hypothesis that people will find it less plausible that AI is capable of judging the morality conveyed by a behavior compared to judging its competence. Participants estimated the plausibility of AI origin for a set of written impressions of positive and negative behaviors related to morality and competence. Studies 1 and 3 supported our hypothesis that people would be more inclined to attribute AI origin to competence-related impressions compared to morality-related ones. In Study 2, we found this effect only for impressions of positive behaviors. Additional exploratory analyses clarified that the differentiation between the AI origin of competence and morality judgments persisted throughout the first half year after the public launch of popular AI chatbot (i.e., ChatGPT) and could not be explained by participants\' general attitudes toward AI, or the actual source of the impressions (i.e., AI or human). These findings suggest an enduring belief that AI is less adept at assessing the morality compared to the competence of human behavior, even as AI capabilities continued to advance.

The current study tested the hypothesis that the association between musical ability and vocal emotion recognition skills is mediated by accuracy in prosody perception. Furthermore, it was investigated whether this association is primarily related to musical expertise, operationalized by long-term engagement in musical activities, or musical aptitude, operationalized by a test of musical perceptual ability. To this end, we conducted three studies: In Study 1 (N = 85) and Study 2 (N = 93), we developed and validated a new instrument for the assessment of prosodic discrimination ability. In Study 3 (N = 136), we examined whether the association between musical ability and vocal emotion recognition was mediated by prosodic discrimination ability. We found evidence for a full mediation, though only in relation to musical aptitude and not in relation to musical expertise. Taken together, these findings suggest that individuals with high musical aptitude have superior prosody perception skills, which in turn contribute to their vocal emotion recognition skills. Importantly, our results suggest that these benefits are not unique to musicians, but extend to non-musicians with high musical aptitude.

This case study utilized the holistic ecological approach (HEA) to explore a successful athletic talent development environment (ATDE) in China. As a case, we selected a basketball team in one Shanghai sport-friendly high school with outstanding individual and team achievements and aimed at (a) describing the ATDE, and (b) identifying environmental success factors (ESF). Using participant observations, document analysis, informal talks, and formal interviews with key stakeholders, including coaches, teachers, athletes, and administrators from sports and education departments, we derived the ATDE and ESF empirical models. The findings showed that (a) the ATDE demonstrated effective interactions between macro- and micro-levels, and (b) the experienced head coach, dedicated assistant coach, and support from athletes\' parents contributed to overcoming barriers of preconditions (e.g., limited financial and human resources) within the environment. Further, a coherent and robust cultural paradigm led by the head coach helped the environment maintain its success for a long period. Although some features are similar to successful ATDEs in other countries, unique characteristics (e.g., not prioritizing athletes\' autonomy) specific to this ATDE within the Chinese cultural context have been identified. Our findings supplement current studies on ATDEs using the HEA and reflect the environment within Chinese context, offering insights for researchers and practitioners.

This study develops a \"Skill Talent Ecological Evaluation Model\" across cultivation, potential energy, kinetic energy, innovation, and service and support ecologies. AHP-entropy determines indicator weights, Hopfield neural network assesses talent ecology levels, and the PVAR model analyzes digital transformation effects. Findings reveal: Cultivation ecology rates A, potential ecology rates B+, kinetic ecology rates B-, service and support ecology rates B-, and innovation ecology rates C. Digital transformation spurs skill demand, impacting talent and economic contributions. Kinetic ecology sees increased demand, potentially impacting traditional industries positively. Innovation ecology necessitates continuous skill learning. Service and support ecology witnesses growth in digital entrepreneurship, requiring policy incentives and incubation center support.

OBJECTIVE: The objective of this study was to examine the impact of athletes achieving excellence at different ages (excellent age) on their subsequent performance development. The aim was to deepen understanding of the interplay among talent, training, and athletes\' performance development. Additionally, the study aimed to provide insights for athletics coaches to better identify talent and devise more effective personalized long-term training plans.
METHODS: This was a cross-sectional study.
METHODS: A hierarchical linear model was employed to analyze the correlation between excellent age and subsequent performance development in a cohort of 775 elite track and field athletes. This analysis was expanded upon by the application of a general linear regression model, which was used to explore the relationship between excellent age and peak age, peak performance, as well as the growth in performance during adulthood.
RESULTS: As athletes reached excellence at later ages, their peak performance exhibited a U-shaped pattern(p <0.001), initially decreasing and then rising. Simultaneously, their peak age became increasingly advanced(p <0.001), with a progressively larger performance improvement during adulthood(p <0.001). In various disciplines, excellent age is negatively correlated with peak performance for speed athletes(p = 0.025), exhibiting a U-shaped pattern for endurance athletes(p = 0.024), and showing no significant correlation for fast-power athletes(p = 0.916).
CONCLUSIONS: Athletes who achieve excellence either early or later often show more remarkable future developments. However, there are significant distinctions in the age at which these athletes reach their peak performance and the pace of improvement leading up to it. Those who excel early may possess greater innate athletic talent, whereas those who excel later may exhibit superior training adaptability. Consequently, an athlete\'s early performance can predict his/her future performance trajectory, offering support for individualized long-term training plans. In summary, the age at which athletes achieve excellence may bring different advantages to their future athletic performance and development. This implies that we should harness these differences to uncover each athlete\'s maximum potential.

Studies have provided empirical evidence on the prognostic relevance of test batteries and the \"coach\'s eye\" for talent identification. The aims were 1) to compare objective and subjective assessments as well as a combined soccer-specific potential index between future selected and non-selected players and 2) to evaluate the prognostic validity of a multidimensional model as a tool for talent identification in soccer. The sample was composed by 132 male players (14,5 ± 1,4 years; regional competitive level) from U13 to U17 age groups of a Brazilian soccer talent development program. Athletes completed a multidimensional test battery and were subjectively rated by their coaches for sporting potential. Players\' success was evaluated five years later and was operationalized by achieving under-20 category of the Brazilian Championship or adult professional level (success rate, 15.9%). Confirming univariate prognostic validity, future selected outperformed non-selected players regarding 20-m sprint (p = .009), agility (p = .04), countermovement jump (p = .04), sit-and-reach (p = .001), Yo-Yo IR1 (p = .001), dribbling (p < .001), perceived competence (p = .007), peaking under pressure (p = .01), confidence/motivation (p = .03), coping skills (p = .03), intangibles (p < .001) and player potential (p < .001). A combined index (objective tests, athlete\'s assessments and coach\'s eye) named Gold Score Soccer (GSS) showed high prognostic validity (p < .001). A binary logistic regression estimated the probability of success (yes/not) with GSS, ambidextrous and predicted age at peak height velocity as predictors. This multidimensional model named GoldFit Soccer showed high prognostic validity (sensitivity = 85.7%; specificity = 83.8%; accuracy = 84.1%; area under the ROC curve = .93 [.87-.98]). Thus, GoldFit Soccer is a valid multidimensional scientific model for talent identification in soccer.

OBJECTIVE: With the aim to better identify talented Track & Field performance development, this study estimated the relationships between chronological (decimal) age with 60-m sprint, high jump, triple jump, and pole vault performance. Then, to mitigate against expected Relative Age Effects (RAEs), Corrective Adjustment Procedures (CAPs) were applied to an independent sample.
METHODS: Mixed-longitudinal design examining public data between 2005 and 2019.
METHODS: The performances of 5339 Italian sprinters and jumpers (53.1 %) spanning 11.01-17.99 years of age were examined, with trendlines between chronological age and performance established. Related to an independent sample (N = 40,306; female 45.5 %), trendlines were then utilised to apply CAPs and adjust individual performance. Considering raw and adjusted performance data, RAE distributions were examined for the top 25 % and 10 % performers.
RESULTS: For all male and female events, quadratic models best summarised the relationships between chronological age and performance (R2 = 0.74-0.89). When examining independent athletes in similar event, RAEs were more pronounced in males (Cramer\'s V = 0.35-0.14) than females (Cramer\'s V = 0.29-0.07). For both sexes, RAE magnitude decreased with age and increased according to performance level (i.e., Top25%-Top10%). However, following CAP applications, RAEs were reduced or removed within annual age groups and performance levels.
CONCLUSIONS: With RAEs prevalent across Italian youth Track & Field events, findings validate CAPs as a strategy to account for the influence of relative age differences on athletic performance. CAPs help establish a more equitable strategy for performance evaluation and could help improve the efficacy of long-term athlete development programming.

When students with high cognitive abilities disengage from school, this implies a severe loss of talent to students themselves and to society. Hence, it is important to understand how teachers can prevent disengagement and underachievement in high-ability students. Whereas a large body of research has demonstrated that need-supportive teaching (i.e., the provision of autonomy support, involvement, and structure) and differentiated instruction relate positively to students\' academic development, it remains unclear whether such practices would be equally, more, or less beneficial for high-ability students. Drawing on data from a longitudinal four-wave study among early adolescents from Flanders (N = 3586), this study showed that need-supportive teaching in math classes was positively associated with intrinsic motivation, behavioral engagement, and math performance in high-ability students, both at the level of between-student differences and at the level of changes in students over time. Standardized estimates were typically between 0.05 and 0.20 at the between-person level, indicating small effect sizes, with more modest effect sizes at the within-person level. Importantly, these associations were found to be generally equivalent across high- and average-ability students. Comparing the provision of need-supportive teaching to either high- or average-ability students, high-ability students particularly reported more autonomy support from their math teachers than average-ability students, with small effect sizes (i.e., Cohen\'s d between 0.16 and 0.27). These findings underline the importance of need-supportive teaching to support the motivational and academic development of both high- and average-ability students.

UNASSIGNED: Biological maturity and relative age player selection biases are well documented in youth sports. However, there has been limited examination of the relationship between these biases.
UNASSIGNED: This study investigated the presence, strength, and independence of relative age and biological maturity selection biases in Gaelic football.
UNASSIGNED: A total of 247 male players from U14 to U16, from two talent academies were assessed for relative age (decimal age (DA)) and biological maturity (discrepancy between biological and chronological age (BA-CA)).
UNASSIGNED: Relative age effects (RAE) were observed in the U14 (DA = 0.62, d = 0.40) and U15 squads (DA = 0.57. d = 0.26) only. A bias towards advanced maturity status was present at U14 (BA-CA = 0.60, d = 0.83), U15 (BA-CA = 0.78, d = 0.89), and U16 (BA-CA, d = 1.01). There was a trivial (U14, r(83) = -0.210; U15, r(88) = 0.060) and low (U16, r(76) = 0.352) correlation between relative age and maturity status.
UNASSIGNED: Substantial maturity selection biases and, to a lesser degree, relative age biases are evident in youth Gaelic football. Critically, these biases are independent constructs. Coaches and policy makers should be educated on the distinct influences of relative age and maturation, and on strategies to address these biases.