{"id":"W4390618942","doi":"10.1167/iovs.65.1.17","title":"Applying Resampling and Visualization Methods in Factor Analysis to Model Human Spatial Vision","year":2024,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"McGill University Health Centre; National Natural Science Foundation of China; McGill University","keywords":"Achromatic lens; Resampling; Visualization; Sensitivity (control systems); Computer science; Contrast (vision); Chromatic scale; Artificial intelligence; Population; Confirmatory factor analysis; Pattern recognition (psychology); Statistics; Data mining; Mathematics; Machine learning; Optics; Structural equation modeling; Engineering","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":[0.03576273,0.002282765,0.001186632,0.004264212,0.001042269,0.002745476,0.001989315,0.001139633,0.00635392],"category_scores_gemma":[0.1427735,0.000746879,0.003692953,0.002855672,0.001684587,0.002214848,0.002268524,0.002371198,0.001512782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114701,"about_ca_system_score_gemma":0.002175506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007741744,"about_ca_topic_score_gemma":0.007225354,"domain_scores_codex":[0.9818234,0.01452754,0.0007348889,0.001449969,0.00123197,0.0002322],"domain_scores_gemma":[0.92805,0.05480386,0.003204683,0.008992348,0.004460512,0.0004886609],"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":[0.0006392684,0.0003899122,0.03571552,0.001718037,0.003083011,0.0007309417,0.00605535,0.1447336,0.007818424,0.09435862,0.03204875,0.6727086],"study_design_scores_gemma":[0.0002618594,0.000340689,0.01903694,0.0004926932,0.0003952702,0.0004204955,0.0006238176,0.7635136,0.006797542,0.1762919,0.03150232,0.0003230483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009926049,0.0002454063,0.9854049,0.0002499884,0.000136677,0.0002303933,0.0003982014,0.002734826,0.0006734696],"genre_scores_gemma":[0.08257548,0.0002401606,0.9130949,0.00009044454,0.0001032641,0.001416567,0.0008987079,0.001202229,0.0003782653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03576273,"threshold_uncertainty_score":0.1891336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172181286322441,"score_gpt":0.5114173280148256,"score_spread":0.3941991993825816,"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."}}