Results 231 to 240 of about 906,571 (334)

Are False Memory and Creative Thinking Mediated by Common Neural Substrates? An fMRI Meta-Analysis. [PDF]

Creat Res J
Thakral PP, Starkey CC, Devitt AL, Schacter DL.   +3 more
europepmc   +1 more source

Differential Contributions of Prefrontal, Medial Temporal, and Sensory-Perceptual Regions to True and False Memory Formation [PDF]

, 2006
Hongkeun Kim, Roberto Cabeza
openalex   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source

Representation of shared surface information and false memory for abstract versus concrete pictures in the conjoint recognition paradigm. [PDF]

Psychol Res
Nieznański M, Ford D, Obidziński M.
europepmc   +1 more source

Reading comprehension in adults: component skills; false memories; and judgements of coherence

, 2011
Stephen T. Hamilton
openalex  

How Does Negative Emotion Cause False Memories?

, 2008
Charles J. Brainerd, Lílian Milnitsky Stein, Ronie Alexsandro Teles da Silveira, Gustavo Rohenkohl, Valerie F. Reyna   +4 more
openalex   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

From vector spaces to DRM lists: False Memory Generator, a software for automated generation of lists of stimuli inducing false memories. [PDF]

Behav Res Methods
Petilli MA, Marelli M, Mazzoni G, Marchetti M, Rinaldi L, Gatti D.   +5 more
europepmc   +1 more source

False memories [PDF]

Advances in Psychiatric Treatment, 1999
openaire   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source