{"id":"W2895228715","doi":"10.2352/cic.2015.23.1.art00014","title":"Robust Chroma and Lightness Descriptors","year":2015,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Categorization, perception, and language","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Studies; University of British Columbia","funders":"","keywords":"Standard illuminant; Lightness; Mathematics; Artificial intelligence; Pattern recognition (psychology); Computer vision; Computer science","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":[0.0009631505,0.000751975,0.0008197141,0.004563923,0.0004236975,0.002325424,0.0009406463,0.0005401143,0.007663205],"category_scores_gemma":[0.005303404,0.0002440098,0.0009510109,0.003418616,0.0007690199,0.001948144,0.001404426,0.001169679,0.002980796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001015335,"about_ca_system_score_gemma":0.0008123596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147182,"about_ca_topic_score_gemma":0.002990943,"domain_scores_codex":[0.9986452,0.0001088054,0.00007907847,0.0003064992,0.0007030357,0.0001574737],"domain_scores_gemma":[0.9971438,0.000491806,0.0004658764,0.0006224925,0.001119683,0.0001564293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001814241,0.0003775773,0.02448086,0.0005322173,0.0004140711,0.0002500716,0.0002033936,0.02406785,0.151058,0.0309844,0.0153055,0.7505118],"study_design_scores_gemma":[0.0002379009,0.001021686,0.2661323,0.0002408756,0.0005292488,0.001904341,0.0006944939,0.4479116,0.168042,0.04220764,0.07008201,0.0009958408],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2283726,0.002279245,0.7200413,0.0002710424,0.0006455949,0.000432613,0.01094399,0.006548863,0.03046479],"genre_scores_gemma":[0.7594367,0.0007274318,0.2206644,0.0001387581,0.0002748647,0.0003373405,0.01089934,0.0006861935,0.006835046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007663205,"threshold_uncertainty_score":0.02563602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08235764575415004,"score_gpt":0.2935960342998326,"score_spread":0.2112383885456826,"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."}}