{"id":"W2460562411","doi":"10.1002/hbm.23285","title":"Dynamic functional connectivity shapes individual differences in associative learning","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Montreal Neurological Institute and Hospital; Baycrest Hospital","funders":"Canadian Institutes of Health Research; James S. McDonnell Foundation","keywords":"Psychology; Dynamic functional connectivity; Cognition; Cognitive psychology; Neuroscience; Neuropsychology; Associative learning; Functional connectivity","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009585879,0.0002566263,0.0003408109,0.000354245,0.0008708508,0.00008613734,0.0002414764,0.0001004452,0.0003185617],"category_scores_gemma":[0.01990688,0.0002061599,0.00009841712,0.000427251,0.0002900597,0.0004545759,0.0002661221,0.0003887994,0.0001010037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003385631,"about_ca_system_score_gemma":0.00005257461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002455502,"about_ca_topic_score_gemma":0.0003084868,"domain_scores_codex":[0.9971126,0.0007048766,0.0003003244,0.0008131996,0.000569518,0.0004994783],"domain_scores_gemma":[0.9806657,0.01888805,0.0002116382,0.0001208487,0.00005389084,0.00005982218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003369019,0.0001511016,0.3191253,0.00002122765,0.00005534127,0.00002323731,0.002456935,0.0000397329,0.6561373,0.01696537,0.001433766,0.003556995],"study_design_scores_gemma":[0.0008770512,0.0001000865,0.9841686,0.0001186346,0.000004631158,0.000006222891,0.0006689043,0.0003589487,0.0004615418,0.01178213,0.00113896,0.0003142768],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843962,0.00002533221,0.002576328,0.009352858,0.0002302778,0.0002283599,0.00002334076,0.0002152785,0.00295205],"genre_scores_gemma":[0.9958548,0.000005641495,0.00003453431,0.001593334,0.0001013791,0.00007491668,0.000002671819,0.00002293946,0.002309783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6650434,"threshold_uncertainty_score":0.9883488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08376222202942145,"score_gpt":0.2770748256660828,"score_spread":0.1933126036366613,"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."}}