{"id":"W4280610424","doi":"10.1364/oe.456067","title":"Adapting to an enhanced color gamut – implications for color vision and color deficiencies","year":2022,"lang":"en","type":"article","venue":"Optics Express","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Eye Institute","keywords":"Gamut; Color vision; Color gel; Chromatic adaptation; Optics; Contrast (vision); Spectral color; Color space; Computer vision; Computer science; Color constancy; Artificial intelligence; Color filter array; Color difference; Lightness; Filter (signal processing); RGB color model; Perception; Color balance; Adaptation (eye); Color model; Physics; Color image; Image processing; Psychology","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":[0.0005050275,0.0004211112,0.0001878001,0.0003428083,0.0002385754,0.0006853761,0.0003855501,0.0004070555,0.001188098],"category_scores_gemma":[0.001816,0.0002676581,0.0002028444,0.0001210631,0.001278599,0.0008806663,0.0008317092,0.0007478512,0.00007999214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003970562,"about_ca_system_score_gemma":0.0002738021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0011459,"about_ca_topic_score_gemma":0.000787119,"domain_scores_codex":[0.9997576,0.00006116094,0.0000161957,0.00005936305,0.00006887811,0.00003674259],"domain_scores_gemma":[0.9993594,0.0001750214,0.0001508885,0.0001183508,0.00009254548,0.0001036845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003752691,0.00007910128,0.006211662,0.00004362621,0.00001054454,0.0002679951,0.0002098248,0.00125101,0.9821191,0.001836585,0.00008728159,0.007508038],"study_design_scores_gemma":[0.000112337,0.001139513,0.3187142,0.00005603408,0.00006410195,0.004371657,0.001242498,0.02394416,0.6253201,0.02290604,0.002037951,0.00009146113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920642,0.0001032578,0.006520118,0.0001861302,0.000008847897,0.00001153088,0.00002035386,0.00005140055,0.001034258],"genre_scores_gemma":[0.9956366,0.00008775256,0.003946246,0.00005640699,0.000002012872,0.00001005988,0.00001389745,0.00001685686,0.0002301639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001188098,"threshold_uncertainty_score":0.003974617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08611380842342382,"score_gpt":0.3684182357744362,"score_spread":0.2823044273510124,"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."}}