{"id":"W1199517114","doi":"10.1016/j.jmp.2017.06.001","title":"Addressing very short stimulus encoding times in modeling schizophrenia cognitive deficit","year":2017,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research","keywords":"Encoding (memory); ENCODE; Computer science; Stimulus (psychology); Cognition; Cognitive model; Schizophrenia (object-oriented programming); Cognitive psychology; Psychology; Artificial intelligence; Neuroscience; Gene; Genetics; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003929859,0.0003132157,0.0002239965,0.0002462049,0.0001489522,0.0004683968,0.0005192737,0.0006546479,0.001090209],"category_scores_gemma":[0.003487522,0.0001602577,0.0002294332,0.0001407856,0.000258576,0.000606732,0.0003945978,0.0006809213,0.00006300331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005416759,"about_ca_system_score_gemma":0.0007763659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006138749,"about_ca_topic_score_gemma":0.004926721,"domain_scores_codex":[0.9999374,0.00001916884,0.000004143743,0.00001130618,0.000008121919,0.00001977112],"domain_scores_gemma":[0.9987827,0.0008387899,0.0001664805,0.00006482785,0.0000673251,0.00008002591],"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":[0.0006843009,0.0003308367,0.01032897,0.00009094587,0.00006548642,0.0003795176,0.0001545873,0.9288622,0.0310567,0.01059098,0.0003185568,0.01713693],"study_design_scores_gemma":[0.000009645936,0.00004819166,0.001429844,0.000003430061,0.00001168591,0.00002089105,0.00002022603,0.9945563,0.001897214,0.001937147,0.00005969115,0.000005752249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624799,0.00005746385,0.0365532,0.0001138836,0.00001455476,0.00001370314,0.00005858515,0.00004917014,0.0006596288],"genre_scores_gemma":[0.997282,0.00002005759,0.002447351,0.000005376831,0.0000020579,0.000009555666,0.00001692238,0.000007290103,0.0002093705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006138749,"threshold_uncertainty_score":0.01220602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1790942280151065,"score_gpt":0.4050685124815691,"score_spread":0.2259742844664626,"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."}}