{"id":"W4293202069","doi":"10.1561/2600000027","title":"Adaptive Internal Models in Neuroscience","year":2022,"lang":"en","type":"article","venue":"Foundations and Trends® in Systems and Control","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Neuroscience; Computational neuroscience; Cognitive science; Psychology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001766701,0.00006684052,0.0001127096,0.0001775285,0.0002212753,0.000171301,0.0001979499,0.00001154326,0.000004161225],"category_scores_gemma":[0.000001718365,0.00006204142,0.00001507719,0.0004844236,0.00003205255,0.000313482,0.0001216649,0.0001172535,4.114792e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002310213,"about_ca_system_score_gemma":0.00001256868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005643189,"about_ca_topic_score_gemma":0.0001653063,"domain_scores_codex":[0.9992323,0.00006878996,0.0001813182,0.0002709189,0.000106846,0.0001398498],"domain_scores_gemma":[0.9997066,0.00004593892,0.00005378577,0.0001400339,0.00001237373,0.00004125382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001237792,0.0001012876,0.002819313,0.000003311183,0.000004050093,0.00001706263,0.000539111,0.05270345,0.00009097922,0.8371072,0.0001509737,0.1064509],"study_design_scores_gemma":[0.000544032,0.00005832959,0.01072482,0.00000665813,0.000001528239,0.00003172123,0.00009829031,0.9812615,2.27778e-7,0.003304838,0.003894167,0.00007390857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1168709,0.001861805,0.86952,0.004115074,0.0008440243,0.0006046707,0.00005726978,0.00008471825,0.006041553],"genre_scores_gemma":[0.9991413,0.00001347417,0.0001171745,0.0001391361,0.00002018162,0.0002323193,0.000001634406,0.000002671685,0.0003320537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9285581,"threshold_uncertainty_score":0.2529976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807900556773028,"score_gpt":0.2550144430613092,"score_spread":0.2269354374935789,"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."}}