{"id":"W2065528056","doi":"10.3758/bf03196707","title":"Merging race models and adaptive networks: A parallel race network","year":2004,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Race (biology); Generalization; Network model; Cognition; Metric (unit); Computer science; Psychology; Theoretical computer science; Artificial intelligence; Mathematics; Sociology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004979309,0.0002931568,0.0005052826,0.00003300457,0.0002407706,0.0000692912,0.0002393526,0.00007228552,0.000137701],"category_scores_gemma":[0.00007768362,0.0002620986,0.0001446972,0.0002520974,0.00009977049,0.0001202089,0.0001020098,0.0003216453,0.0002195018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005267196,"about_ca_system_score_gemma":0.00002296339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002185728,"about_ca_topic_score_gemma":0.000004082422,"domain_scores_codex":[0.9979464,0.0001829322,0.0004727137,0.0007720697,0.0001441974,0.0004816632],"domain_scores_gemma":[0.9989541,0.0002032256,0.0002660216,0.0003979515,0.00002360144,0.0001550934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003606353,0.000222805,0.00003526267,0.0008462564,0.00005584683,0.00005167114,0.0001266702,0.668418,0.0007617337,0.1122139,0.1059573,0.1109499],"study_design_scores_gemma":[0.002120556,0.0002766443,0.0001589554,0.006191722,0.0001471977,0.0002531717,0.00001646418,0.09284347,0.00002836544,0.02156213,0.8752782,0.00112313],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02069936,0.5645767,0.2618208,0.1172325,0.005390928,0.006047425,0.00002291164,0.0007311591,0.02347815],"genre_scores_gemma":[0.2228957,0.7265655,0.008915037,0.03855656,0.000808899,0.0002648692,0.000007734783,0.0001123258,0.001873401],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7693209,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03647958606093415,"score_gpt":0.2659592116790338,"score_spread":0.2294796256180996,"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."}}