{"id":"W3014744909","doi":"10.1002/col.22499","title":"Color vision defectives' experience: When white is green","year":2020,"lang":"en","type":"article","venue":"Color Research & Application","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Defence Research and Development Canada; King Saud University","keywords":"Color vision; Context (archaeology); Artificial intelligence; White (mutation); Icon; Computer vision; Computer science; Psychology; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005613088,0.0003223216,0.000292451,0.0006946262,0.0005115645,0.0009422603,0.0002494129,0.0006365463,0.00288193],"category_scores_gemma":[0.003916025,0.0001925168,0.0001583631,0.0001984597,0.00118972,0.0005186385,0.000917602,0.0008373963,0.0001827494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002890876,"about_ca_system_score_gemma":0.000148021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005580153,"about_ca_topic_score_gemma":0.003800165,"domain_scores_codex":[0.9995734,0.0001046378,0.00002226917,0.00006917967,0.0001506364,0.00007991104],"domain_scores_gemma":[0.9986179,0.0004766274,0.000418253,0.0001335911,0.0001355539,0.0002180971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001443432,0.0007625643,0.666317,0.0002507206,0.00009377254,0.01359482,0.1446306,0.0004777214,0.1252111,0.001704216,0.003423207,0.04209067],"study_design_scores_gemma":[0.00004705442,0.001439036,0.8615419,0.0001325886,0.00008817211,0.01906306,0.1002306,0.001334638,0.009737814,0.001435494,0.004837125,0.0001125241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988058,0.00004910485,0.000066986,0.00004994378,0.000007328309,0.000002813645,0.00001121452,0.00000609581,0.001000657],"genre_scores_gemma":[0.9995161,0.00003018082,0.00007511501,0.00002789354,0.000001696297,0.000001451536,0.00001033819,0.000002528646,0.0003346735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005580153,"threshold_uncertainty_score":0.01109535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2123070534709483,"score_gpt":0.4661155408844314,"score_spread":0.2538084874134831,"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."}}