{"id":"W4413965048","doi":"10.1162/imag.a.156","title":"Mapping individual differences in intermodal coupling in neurodevelopment","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Connaught Fund; University of Toronto; McLaughlin Centre, University of Toronto; National Alliance for Research on Schizophrenia and Depression; Regeneron Pharmaceuticals; National Institute of Biomedical Imaging and Bioengineering; University of Pennsylvania; Brain and Behavior Research Foundation","keywords":"Coupling (piping); Psychology; Computer science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001023344,0.0002062546,0.0002004044,0.0003692695,0.0001752739,0.0001159615,0.0006929988,0.00003053054,0.00005836548],"category_scores_gemma":[0.0003788166,0.0002173809,0.00002556148,0.00132865,0.0004508985,0.0005114957,0.000811666,0.0004480551,0.00004388767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000336693,"about_ca_system_score_gemma":0.00006174341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003564419,"about_ca_topic_score_gemma":0.0001300146,"domain_scores_codex":[0.9972706,0.0001001542,0.0004418214,0.001023595,0.0004607774,0.0007030253],"domain_scores_gemma":[0.9993914,0.0001527302,0.00008628507,0.0002745326,0.000003322929,0.00009168114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003034675,0.00006467,0.9715496,0.000008568282,2.961064e-7,0.0000651161,0.0007181345,0.001560079,0.0144665,0.00001933999,0.00002701432,0.01151768],"study_design_scores_gemma":[0.0002748554,0.00000787713,0.9352488,0.0001169818,0.000001054097,0.000004930295,0.000243636,0.06250165,0.000613686,0.0002398378,0.0005670453,0.0001796705],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908758,0.00002656288,0.003784038,0.001525629,0.0004054702,0.000322389,0.00000214664,0.00004471677,0.003013263],"genre_scores_gemma":[0.9955339,0.00003502554,0.0004186133,0.003832623,0.00000687494,0.00004147792,8.074153e-7,0.00001045757,0.0001201719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06094157,"threshold_uncertainty_score":0.8864534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02527462173988821,"score_gpt":0.2672933457847896,"score_spread":0.2420187240449014,"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."}}