{"id":"W3122269555","doi":"10.1101/2021.01.15.426915","title":"Learning from unexpected events in the neocortical microcircuit","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Vector Institute; Canadian Institute for Advanced Research; University of Toronto; Mila - Quebec Artificial Intelligence Institute; The Scarborough Hospital; York University","funders":"Compute Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Neocortex; Neuroscience; Calcium imaging; Stimulus (psychology); Visual cortex; Bursting; Apical dendrite; Sensory system; Nerve net; Biology; Psychology; Cerebral cortex; Calcium; Chemistry; Cognitive psychology","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":[0.000373614,0.0004298645,0.0004240971,0.0001641686,0.000217142,0.0002976885,0.0007956793,0.0003991198,0.00006728731],"category_scores_gemma":[0.001270535,0.0003808312,0.0001734311,0.000805678,0.00008845489,0.0001516764,0.0004789576,0.001884513,0.00005758467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001949177,"about_ca_system_score_gemma":0.0002739271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001732338,"about_ca_topic_score_gemma":0.00001238158,"domain_scores_codex":[0.9963707,0.0007682717,0.0004994885,0.001278765,0.0005457125,0.0005370651],"domain_scores_gemma":[0.9981367,0.0004257188,0.0002795409,0.000917881,0.000118717,0.000121424],"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":[0.00001472165,0.0001414268,0.01051604,0.00003552977,0.00001391376,0.0001973803,0.00003913421,0.0002088139,0.9885786,0.0002305276,0.00002083985,0.000003046],"study_design_scores_gemma":[0.0007139052,0.00007427704,0.5108765,0.0004101694,0.00007828676,8.805884e-8,0.00003458933,0.006361701,0.4793983,0.00002405624,0.00107225,0.0009558281],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968974,0.0001347184,0.0004569901,0.0004560485,0.0012773,0.000528179,0.00003778091,0.0001985791,0.00001301],"genre_scores_gemma":[0.9982268,0.0001190458,0.0001478499,0.000969376,0.0003200731,0.0001325448,8.500812e-7,0.00007687461,0.000006549506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5091803,"threshold_uncertainty_score":0.9998643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0238216342738093,"score_gpt":0.2250273099866655,"score_spread":0.2012056757128562,"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."}}