{"id":"W1127806665","doi":"","title":"Supra–Threshold Contrast Matching With Macular Disorders","year":2006,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Contrast (vision); Matching (statistics); Ophthalmology; Medicine; Optometry; Physics; Optics; Pathology","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":[0.0008066741,0.0007932981,0.0005646169,0.002489205,0.001167572,0.001093129,0.0008119479,0.001488209,0.00956093],"category_scores_gemma":[0.007465553,0.0003554589,0.0003999761,0.001759806,0.001419338,0.002004305,0.001187291,0.0009659762,0.0009666851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005425197,"about_ca_system_score_gemma":0.0007645678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002081222,"about_ca_topic_score_gemma":0.001449224,"domain_scores_codex":[0.9989397,0.0001421353,0.0002164872,0.0002238102,0.0002523142,0.0002255664],"domain_scores_gemma":[0.9952545,0.001566657,0.001839981,0.00068513,0.0003008691,0.0003529617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007620586,0.0008729058,0.4893578,0.0002269044,0.0001444589,0.4216639,0.0008343305,0.0006675628,0.02489839,0.006866734,0.003029108,0.04381742],"study_design_scores_gemma":[0.00008590902,0.0004929514,0.2319171,0.00002832203,0.00007690545,0.7527298,0.0002992249,0.001488292,0.005927047,0.005767594,0.00115638,0.00003042956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796933,0.000603049,0.001501868,0.0007330204,0.00008136624,0.00008274877,0.0002541823,0.00007862361,0.01697181],"genre_scores_gemma":[0.9986839,0.00007860332,0.0003231344,0.0001334648,0.00009234042,0.000006262355,0.00005521981,0.00001465042,0.0006123767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00956093,"threshold_uncertainty_score":0.03198457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01512126160047533,"score_gpt":0.298054611800673,"score_spread":0.2829333502001977,"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."}}