{"id":"W2003955778","doi":"10.1002/hbm.21069","title":"Population neuroscience: Why and how","year":2010,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":156,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Baycrest Hospital; University of Toronto; Montreal Neurological Institute and Hospital","funders":"National Institutes of Health; Canadian Institutes of Health Research; European Commission; Royal Society","keywords":"Population; Neuroscience; Cognitive neuroscience; Psychology; Neuroimaging; Observational study; Causality (physics); Imaging genetics; Cognition; Cognitive science; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001222502,0.0003840919,0.0006625958,0.0001445769,0.0007313816,0.0001777434,0.0003485963,0.0002793508,0.0003853576],"category_scores_gemma":[0.0002856424,0.000366887,0.0001210074,0.0002950432,0.0003352684,0.0003488557,0.0004341237,0.0008349948,0.0001397656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002144394,"about_ca_system_score_gemma":0.00001323746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008633961,"about_ca_topic_score_gemma":0.00006560313,"domain_scores_codex":[0.9973101,0.0003571032,0.0003226131,0.001082567,0.0004155499,0.0005120419],"domain_scores_gemma":[0.9987639,0.0001700814,0.0003633961,0.0004914548,0.000002508669,0.0002086672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[1.43583e-7,0.00001503499,0.0008044178,0.001171823,0.000002889143,0.00001264329,0.0001517579,0.000001252783,0.0005010837,0.00009993395,0.00131842,0.9959206],"study_design_scores_gemma":[0.00006570186,0.00001529999,0.02152573,0.001062674,0.00002956126,0.00002874091,0.00001863331,0.00002951962,1.329643e-7,0.0002286299,0.9766321,0.000363284],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003788261,0.9789569,0.002240353,0.002123175,0.0006710241,0.00344743,0.00003079525,0.0002608718,0.008481212],"genre_scores_gemma":[0.001242145,0.9934558,0.0004886497,0.002420136,0.0002591732,0.0001035774,0.00008321213,0.00009610301,0.001851204],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9955573,"threshold_uncertainty_score":0.9998783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07575303010441693,"score_gpt":0.3264931260752852,"score_spread":0.2507400959708683,"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."}}