{"id":"W1989514335","doi":"10.1017/s0140525x0539008x","title":"is color perception really categorical?","year":2005,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Categorization, perception, and language","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Categorization; Categorical variable; Accidental; Margin (machine learning); Perception; Psychology; Product (mathematics); Cognitive psychology; Categorical perception; Computer science; Communication; Social psychology; Artificial intelligence; Mathematics; Machine learning; Neuroscience; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00192748,0.0002102827,0.0005395274,0.0009884038,0.0008704297,0.004252537,0.001177502,0.00184317,0.007566044],"category_scores_gemma":[0.01357942,0.000245839,0.0004612474,0.0009598141,0.01110012,0.006627255,0.001501015,0.00208331,0.001602424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000893564,"about_ca_system_score_gemma":0.0004728289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001772812,"about_ca_topic_score_gemma":0.0009747592,"domain_scores_codex":[0.9984011,0.0004192791,0.0000522878,0.0005290094,0.0004190972,0.0001792791],"domain_scores_gemma":[0.9948494,0.002032511,0.0006019681,0.001095024,0.001082,0.0003391394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001739866,0.0000397568,0.01402363,0.0002943483,0.00007024553,0.000134371,0.002028531,0.0005994974,0.008920337,0.887512,0.006873252,0.07932999],"study_design_scores_gemma":[0.0000149396,0.00004775825,0.01600118,0.00006673422,0.00002403117,0.0003078405,0.001212924,0.001615903,0.00149264,0.9613928,0.01776988,0.0000533347],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3707608,0.009800408,0.2358033,0.09351087,0.003466832,0.00004767081,0.001393832,0.0009745921,0.2842416],"genre_scores_gemma":[0.9837331,0.0009966872,0.008271256,0.002595089,0.0004282214,0.00002603319,0.0001898873,0.00007355442,0.003686198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007566044,"threshold_uncertainty_score":0.02531093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06195809667461378,"score_gpt":0.3879065027582321,"score_spread":0.3259484060836183,"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."}}