{"id":"W4392005698","doi":"10.1016/j.neuroimage.2024.120552","title":"Identifying individual's distractor suppression using functional connectivity between anatomical large-scale brain regions","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fundamental Research Funds for the Central Universities; Sichuan Province Science and Technology Support Program; National Natural Science Foundation of China","keywords":"Functional magnetic resonance imaging; Psychology; Resting state fMRI; Functional connectivity; Cognition; Neuroscience; Insula; Prefrontal cortex; Correlation; Neuroimaging; Cognitive psychology; Audiology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002893404,0.0003660335,0.000238698,0.0005407259,0.0001303478,0.0003520497,0.0001882079,0.0002296589,0.0008302464],"category_scores_gemma":[0.001666276,0.0001291744,0.0002768763,0.0002644604,0.000171648,0.0002799186,0.0002380593,0.0002268806,0.0001144321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002023477,"about_ca_system_score_gemma":0.0001992156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004164634,"about_ca_topic_score_gemma":0.008216463,"domain_scores_codex":[0.9998965,0.00002081511,0.000004676872,0.00005260448,0.0000131812,0.00001219798],"domain_scores_gemma":[0.999595,0.0001897164,0.00009909621,0.00004682317,0.00003257665,0.00003684661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008986824,0.0002933565,0.8021,0.0001572757,0.0006598563,0.0008183455,0.00120572,0.03337689,0.0943566,0.002210224,0.0008584567,0.0630646],"study_design_scores_gemma":[0.00001175594,0.0002448579,0.8667861,0.000015978,0.0001271787,0.0006299718,0.0001895532,0.1243459,0.004078063,0.003096514,0.0004482852,0.0000259263],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856827,0.00009413587,0.01315002,0.00003690131,0.000003354573,0.00002186939,0.0004095386,0.00004206994,0.0005594087],"genre_scores_gemma":[0.9979729,0.00003459617,0.0016305,0.000004086399,0.000002239224,0.00001153834,0.0002258445,0.00000479386,0.0001135387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004164634,"threshold_uncertainty_score":0.008280814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207889488943068,"score_gpt":0.3393213808422434,"score_spread":0.2185324319479366,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}