{"id":"W2903352281","doi":"10.1371/journal.pcbi.1006565","title":"Atlases of cognition with large-scale human brain mapping","year":2018,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"RWTH Aachen University; Horizon 2020 Framework Programme; Deutsche Forschungsgemeinschaft; National Science Foundation; Institut national de recherche en informatique et en automatique (INRIA); Agence Nationale de la Recherche","keywords":"Inference; Cognition; Neuroimaging; Computer science; Cognitive map; Functional neuroimaging; Function (biology); Neural substrate; Brain mapping; Artificial intelligence; Elementary cognitive task; Atlas (anatomy); Cognitive neuroscience; Cognitive science; Neuroscience; Psychology; Biology","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":[0.001414719,0.0006900922,0.0004790373,0.002818516,0.0005680781,0.002451663,0.001020158,0.0008501865,0.003492678],"category_scores_gemma":[0.004772024,0.0005757509,0.0009962711,0.00221283,0.001510853,0.001511503,0.002482116,0.001268663,0.0007538296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008589292,"about_ca_system_score_gemma":0.0009924098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002160477,"about_ca_topic_score_gemma":0.004040239,"domain_scores_codex":[0.9994166,0.0001999705,0.00004280127,0.0001896382,0.0001159184,0.00003509861],"domain_scores_gemma":[0.9981943,0.0007345177,0.0002331975,0.0006357813,0.0001389065,0.00006328253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004109422,0.0001327014,0.01179194,0.001385545,0.0007897901,0.0008329937,0.00241395,0.2117102,0.1235795,0.3274867,0.01674284,0.302723],"study_design_scores_gemma":[0.00006557948,0.0001300036,0.02936905,0.0001514788,0.0002052012,0.00140912,0.0005549215,0.3373276,0.03224391,0.5435813,0.0548171,0.0001447475],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01649443,0.000311109,0.9774965,0.0001833598,0.00002522287,0.00007403023,0.001438556,0.001067761,0.002909098],"genre_scores_gemma":[0.3337068,0.0006979819,0.6596184,0.0001471331,0.00006553639,0.0005961858,0.002969349,0.0009309759,0.001267659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003492678,"threshold_uncertainty_score":0.01168418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05547541584445604,"score_gpt":0.2886244958317574,"score_spread":0.2331490799873014,"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."}}