Results 141 to 150 of about 9,507,745 (249)

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

open access: yesAdvanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler   +7 more
wiley   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

open access: yesAdvanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin   +4 more
wiley   +1 more source

Editorial: Advancing research on teachers' professional vision: implementing novel technologies, methods and theories

open access: yesFrontiers in Education
Christian Kosel   +3 more
doaj   +1 more source

Impact of digitalization-related STEM in-service teacher trainings in cooperation with out-of-school student labs on teachers' professional knowledge, self-efficacy and technology commitment. [PDF]

open access: yesFront Psychol
Reher A   +9 more
europepmc   +1 more source

Developing a Conceptual Framework for Understanding Professional Knowledge

open access: yes, 2011
Our conceptual framework tries to capture the complexities which arise when different national and regional contexts intersect with different professional settings and generational and historical periodisations.
Goodson, Ivor, Lindblad, Sverker,
core  

Current Standards of Monitoring Models in Healthcare Settings

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay   +5 more
wiley   +1 more source

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