{"id":"W2664503597","doi":"10.1016/j.bbr.2017.06.030","title":"Testing the physiological plausibility of conflicting psychological models of response inhibition: A forward inference fMRI study","year":2017,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Western Hospital; Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychology; Cognition; Anticipation (artificial intelligence); Neuroscience; Cognitive psychology; Stimulus (psychology); Inference; Response inhibition; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.004668138,0.0002081977,0.0004299546,0.0001049382,0.001539785,0.00008932441,0.001221483,0.0001329652,0.00004108486],"category_scores_gemma":[0.01638997,0.0001201225,0.0001262471,0.0003897215,0.003355703,0.000278148,0.00121683,0.0009942133,0.000009782684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003057126,"about_ca_system_score_gemma":0.00003968528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003562636,"about_ca_topic_score_gemma":0.00002909211,"domain_scores_codex":[0.994668,0.002380867,0.0006043646,0.0008169026,0.0009398675,0.0005899685],"domain_scores_gemma":[0.9928543,0.005007884,0.000364974,0.00120824,0.0004648224,0.00009976251],"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":[0.00100344,0.001183883,0.1645477,0.000007895671,0.000003384503,0.00007910721,0.000670159,0.000006331311,0.8303722,0.0001465031,0.0001782886,0.001801197],"study_design_scores_gemma":[0.0008411932,0.002904989,0.9252656,0.00004265722,0.00001101908,0.00002022539,0.0009215785,0.00007926425,0.06770259,0.002075033,0.000003737033,0.0001321229],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948515,0.00001023065,0.000005110546,0.003436885,0.00009425325,0.001097713,0.0000374822,0.00004112649,0.0004257305],"genre_scores_gemma":[0.9995008,0.000002774095,0.0000641144,0.0001217812,0.00003246883,0.0001174836,6.678876e-7,0.00001038111,0.0001495686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7626695,"threshold_uncertainty_score":0.9997601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7896491759968775,"score_gpt":0.5800326532303884,"score_spread":0.209616522766489,"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."}}