{"id":"W3183471211","doi":"","title":"Biologically Constrained Large-Scale Model of the Wisconsin Card Sorting Test","year":2021,"lang":"en","type":"article","venue":"NPARC","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Wisconsin Card Sorting Test; Card sorting; Cognitive flexibility; Robustness (evolution); Prefrontal cortex; Computer science; Neuroscience; Executive functions; Artificial intelligence; Psychology; Basal ganglia; Cognition; Task (project management); Biology; Neuropsychology; Central nervous system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007644771,0.0006183196,0.0007473853,0.0004855574,0.0006672989,0.0009575051,0.002842173,0.002001215,0.004111479],"category_scores_gemma":[0.003148142,0.0005999909,0.0007926747,0.0005721617,0.001502039,0.001723364,0.0008140858,0.001345914,0.0004692622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001532897,"about_ca_system_score_gemma":0.001555396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02473091,"about_ca_topic_score_gemma":0.01545593,"domain_scores_codex":[0.9996817,0.0001296138,0.000009519847,0.00009036539,0.00004452845,0.00004423011],"domain_scores_gemma":[0.9992557,0.0003760699,0.0001329692,0.00004282688,0.0001134537,0.00007900888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002266578,0.00001679505,0.0005461318,0.00001541108,0.00002289439,0.00007126125,0.00003885419,0.9647646,0.0005928628,0.03142171,0.0005198802,0.00196685],"study_design_scores_gemma":[0.000009723358,0.000007448917,0.0002641995,0.000002551984,0.000006168495,0.00001649187,0.000006207976,0.984457,0.00004529405,0.01501037,0.0001681433,0.000006451237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1934046,0.0007727687,0.7678398,0.00517279,0.0001570968,0.0001473008,0.0009344581,0.000541069,0.03103011],"genre_scores_gemma":[0.943705,0.0004281124,0.04106455,0.0003480884,0.00008162226,0.0003415277,0.0003530919,0.00008105073,0.01359686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02473091,"threshold_uncertainty_score":0.04917395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04858564814720982,"score_gpt":0.2574637642847561,"score_spread":0.2088781161375463,"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."}}