{"id":"W3179725962","doi":"","title":"Automated Machine Learning Prediction of Visual Acuity from Preoperative OCT Images After Macular Hole Surgery","year":2021,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Université Laval","funders":"","keywords":"Visual acuity; Medicine; Ophthalmology; Macular hole; Optometry; Surgery; Vitrectomy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009088963,0.0002589226,0.0006671436,0.0002757223,0.0002709545,0.00005920691,0.000143942,0.0001111912,0.0004383004],"category_scores_gemma":[0.002417632,0.0002181406,0.0001878447,0.001636754,0.003504952,0.0004008135,0.0002024506,0.0004440207,0.0000321992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057337,"about_ca_system_score_gemma":0.0007353665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005174461,"about_ca_topic_score_gemma":0.000001936621,"domain_scores_codex":[0.9970778,0.0005650874,0.0004907426,0.0008070827,0.0006352301,0.000424032],"domain_scores_gemma":[0.9980763,0.000341345,0.0002518038,0.0002361934,0.0007846334,0.0003097233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004434722,0.000145397,0.4864406,0.00001793973,0.00007774364,0.0006629381,0.000383636,0.00005764875,0.5120543,0.000001063208,0.00002440777,0.00009002689],"study_design_scores_gemma":[0.000186501,0.0002371212,0.4964953,0.0001450411,0.0001240579,0.0001890235,0.000226729,0.02310237,0.4791009,0.00008186854,0.000006532513,0.0001045564],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981905,0.000479843,0.00002562262,0.0004701864,0.0001281882,0.0001348106,0.00007080854,0.0001440098,0.000356071],"genre_scores_gemma":[0.997733,0.00001953632,0.001391814,0.0001689211,0.00007449042,0.00002503994,0.0001634532,0.00001836751,0.0004053878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03295333,"threshold_uncertainty_score":0.999207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02983719282581518,"score_gpt":0.3388221158356846,"score_spread":0.3089849230098695,"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."}}