{"id":"W4387798955","doi":"10.1097/opx.0000000000002076","title":"Clinical Comparison of High‐resolution and Standard Refractions and Prescriptions","year":2023,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de Sept Iles","funders":"","keywords":"Medical prescription; Optometry; Resolution (logic); Medicine; Computer science; Artificial intelligence; Pharmacology","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":[0.002603196,0.0002471723,0.0004265617,0.0002419725,0.0001897702,0.0003200861,0.0002740042,0.0003716293,0.003744729],"category_scores_gemma":[0.008917488,0.0001729341,0.0004123743,0.0001758663,0.000341089,0.0004458504,0.0002801851,0.0003511176,0.0002717475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002871781,"about_ca_system_score_gemma":0.0002644443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000330307,"about_ca_topic_score_gemma":0.0005576887,"domain_scores_codex":[0.9981411,0.0008378798,0.0002184167,0.0002146586,0.0005253764,0.00006267],"domain_scores_gemma":[0.9936659,0.003364271,0.001840437,0.0003099653,0.0003566781,0.0004627528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.4865368,0.01527378,0.2829929,0.001288887,0.001152763,0.0002430226,0.0008861203,0.000757104,0.03507616,0.0002013781,0.0007164245,0.1748747],"study_design_scores_gemma":[0.01667293,0.3078885,0.6629494,0.00008618012,0.0005984586,0.0005703269,0.0004488381,0.002044159,0.007465082,0.0001211784,0.001097342,0.00005765518],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991042,0.0002273307,0.0001552113,0.00001729552,0.00001139274,0.0000835474,0.00003180141,0.000004100923,0.0003650371],"genre_scores_gemma":[0.9991818,0.0000717661,0.0003965285,0.00001934283,0.00001045879,0.00006475555,0.00004105023,9.906413e-7,0.0002132557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003744729,"threshold_uncertainty_score":0.01376724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08820148706382303,"score_gpt":0.5683388591483419,"score_spread":0.4801373720845189,"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."}}