{"id":"W3138028713","doi":"10.1145/2010324.1964958","title":"Color compatibility from large datasets","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Color perception and design","field":"Psychology","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Hue; Computer science; Artificial intelligence; Color model; Compatibility (geochemistry); Theme (computing); Color space; Set (abstract data type); Computer vision; Image (mathematics); World Wide Web","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002237277,0.0001567261,0.0001740972,0.0001554007,0.0002204177,0.0000142605,0.0003701568,0.0001793071,0.03327664],"category_scores_gemma":[0.0000165436,0.000155068,0.000132481,0.0003258911,0.0001144563,0.00009044483,0.000005654757,0.0003497673,0.001727083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002086778,"about_ca_system_score_gemma":0.00001894682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008009212,"about_ca_topic_score_gemma":0.001701963,"domain_scores_codex":[0.9987316,0.0001900717,0.0002490363,0.000411083,0.0001558776,0.0002623471],"domain_scores_gemma":[0.9982448,0.0002164093,0.00005137235,0.001314487,0.00004085878,0.0001320853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.01416176,0.06421822,0.1507762,0.0001106472,0.003861381,0.0004825758,0.1182104,0.00003867904,0.004104889,0.1532626,0.3091642,0.1816084],"study_design_scores_gemma":[0.003662488,0.0009176138,0.8816524,0.00002065056,0.0002553415,0.00001393012,0.003177334,0.0002430196,0.0006433121,0.02385849,0.08482864,0.0007268622],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7410563,0.00005880725,0.2372722,0.0004567893,0.001975262,0.0006012557,0.00697387,0.0004733515,0.01113212],"genre_scores_gemma":[0.9958891,0.00002043428,0.001832023,0.001689633,0.00002771844,0.00006435134,0.0002668979,0.00001847764,0.0001913676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7308761,"threshold_uncertainty_score":0.9990502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1222335259222588,"score_gpt":0.3418057257478534,"score_spread":0.2195721998255946,"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."}}