{"id":"W3181627517","doi":"10.1016/j.neuron.2021.07.011","title":"The population doctrine in cognitive neuroscience","year":2021,"lang":"en","type":"preprint","venue":"Neuron","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Neurological Disorders and Stroke; Brain and Behavior Research Foundation; National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds de Recherche du Québec - Santé","keywords":"Doctrine; Cognitive neuroscience; Cognition; Population; Cognitive science; Psychology; Neuroscience; Embodied cognition; Educational neuroscience; Cognitive psychology; Sociology; Computer science; Political science; Law; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001130964,0.0005218452,0.0006909292,0.0006964596,0.0006579496,0.002400504,0.0007761646,0.002104824,0.005914601],"category_scores_gemma":[0.00369425,0.0002594712,0.0004862654,0.0008996006,0.004038808,0.006108984,0.001484476,0.002961456,0.001203229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009390049,"about_ca_system_score_gemma":0.0006883033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033272,"about_ca_topic_score_gemma":0.0005598742,"domain_scores_codex":[0.9995727,0.0001688919,0.00001624205,0.00007882092,0.0001337319,0.00002964858],"domain_scores_gemma":[0.9989397,0.0006245867,0.00005729844,0.00013751,0.0001832124,0.00005769136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003080046,0.000002463677,0.00004192225,0.0000128004,0.00000394204,0.00001625784,0.00002700228,0.0004910594,0.0001323317,0.9954681,0.00129971,0.002501207],"study_design_scores_gemma":[0.000002064716,8.595123e-7,0.00004876437,0.000003036404,8.539027e-7,0.00002513867,0.000006946163,0.001996568,0.00003788538,0.9965168,0.001359819,0.000001266494],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06321569,0.01693625,0.5953761,0.04414421,0.002692848,0.00002577439,0.0003987463,0.0005602433,0.2766501],"genre_scores_gemma":[0.8732274,0.007954791,0.06594899,0.00249685,0.006588703,0.0001262451,0.0002863092,0.0004632651,0.04290744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.999342,"threshold_uncertainty_score":0.0197863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05100641016648571,"score_gpt":0.3047436847968551,"score_spread":0.2537372746303694,"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."}}