Results 171 to 180 of about 7,364 (234)

Evaluating and leveraging large language models in clinical pharmacology and therapeutics assessment: From exam takers to exam shapers

open access: yesBritish Journal of Clinical Pharmacology, EarlyView.
Aims In medical education, the ability of large language models (LLMs) to match human performance raises questions about their potential as educational tools. This study evaluates LLMs' performance on Clinical Pharmacology and Therapeutics (CPT) exams, comparing their results to medical students and exploring their ability to identify poorly formulated
Alexandre O. Gérard   +11 more
wiley   +1 more source

From paradise lost to paradise regained: A compassionate retuning of assessed seminars

open access: yesBritish Educational Research Journal, EarlyView.
Abstract Universities often aim to deliver a curriculum that is both research‐based and develops transferable skills in students, thereby enhancing their competitiveness in the job market. At the same time, evidence indicates that university students experience significant stress owing to the competitive nature of the assessments, an aspect that is ...
Sarah Stephen
wiley   +1 more source

Prioritizing Feasible and Impactful Actions to Enable Secure AI Development and Use in Biology

open access: yesBiotechnology and Bioengineering, EarlyView.
ABSTRACT As artificial intelligence continues to enhance biological innovation, the potential for misuse must be addressed to fully unlock the potential societal benefits. While significant work has been done to evaluate general‐purpose AI and specialized biological design tools (BDTs) for biothreat creation risks, actionable steps to mitigate the risk
Josh Dettman   +4 more
wiley   +1 more source

The power of many: when genetics met yeasts and high‐throughput

open access: yesBiological Reviews, EarlyView.
ABSTRACT In recent years, complex technological capabilities have evolved, driven by the need to solve complex and integrative biological questions through global analyses. New equipment allows the scaling up and automation of processes which previously were carried out on a very limited scale.
Víctor A. Tallada, Víctor Carranco
wiley   +1 more source

Machine Learning‐Driven Prediction and Optimization of Cu‐Based Catalysts for CO2 Hydrogenation to Methanol

open access: yesCarbon and Hydrogen, EarlyView.
A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su   +11 more
wiley   +1 more source

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