{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009826988,0.0017101,0.001318731,0.005993445,0.001534041,0.003685676,0.003166579,0.003007285,0.004899699],"category_scores_gemma":[0.06664265,0.000774379,0.002521394,0.005617564,0.001226569,0.005533897,0.00389606,0.003556769,0.002661604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001602528,"about_ca_system_score_gemma":0.0008827287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005275851,"about_ca_topic_score_gemma":0.007363212,"domain_scores_codex":[0.9908457,0.00371129,0.0005611887,0.00218136,0.002366137,0.0003342742],"domain_scores_gemma":[0.9637609,0.0184141,0.001687716,0.01073485,0.004770639,0.0006317523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002805271,0.003083391,0.1481625,0.003146747,0.001860101,0.0008950628,0.000819969,0.1020944,0.01378412,0.02477998,0.2165024,0.482066],"study_design_scores_gemma":[0.000735785,0.0007169845,0.1023237,0.0005564804,0.0005315617,0.001536645,0.001436068,0.6414857,0.01929974,0.1105635,0.1204055,0.0004083913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4831581,0.006146568,0.3232515,0.003358912,0.001421517,0.001229082,0.149048,0.0144591,0.01792724],"genre_scores_gemma":[0.4919743,0.0007788684,0.2838216,0.001201402,0.0003651991,0.001101782,0.2174584,0.0009531754,0.002345278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009826988,"threshold_uncertainty_score":0.05197072,"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."}}