{"id":"W4377232654","doi":"10.1109/tmi.2023.3278269","title":"Panretinal Optical Coherence Tomography","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Retinal Diseases and Treatments","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Eye Institute; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Research to Prevent Blindness","keywords":"Optical coherence tomography; Panretinal photocoagulation; Retina; Peripheral vision; Coherence (philosophical gambling strategy); Computer science; Medical imaging; Retinal; Computer vision; Visualization; Optometry; Optics; Artificial intelligence; Medicine; Ophthalmology; Physics; Diabetic retinopathy","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":[0.00036121,0.0003244207,0.0002413959,0.0007992735,0.0002567598,0.0007803195,0.0004576934,0.0006813296,0.001580067],"category_scores_gemma":[0.0007332804,0.0001631063,0.0001910269,0.000402419,0.0003906843,0.001446072,0.0006737669,0.0007328378,0.0005176974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002521903,"about_ca_system_score_gemma":0.0004152568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003756409,"about_ca_topic_score_gemma":0.0006211385,"domain_scores_codex":[0.9995974,0.00007507958,0.00002255438,0.00008760899,0.0001887749,0.00002873524],"domain_scores_gemma":[0.9996947,0.00006758248,0.00005397444,0.00005191637,0.0001001722,0.00003158873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002066835,0.00009487588,0.004076971,0.0005782,0.00007039672,0.002181212,0.0001489283,0.000917991,0.485092,0.01419179,0.008108455,0.4843326],"study_design_scores_gemma":[0.0001484191,0.001334349,0.01801314,0.0003189916,0.0002443217,0.07477927,0.0002288079,0.04478021,0.4616611,0.01484962,0.3834217,0.0002200138],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08361661,0.06133842,0.8153235,0.004202272,0.00133499,0.0002688098,0.0004798053,0.002399118,0.03103638],"genre_scores_gemma":[0.4690389,0.02434295,0.4899574,0.003222707,0.00121457,0.0002681286,0.0003527874,0.0001946296,0.01140786],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001580067,"threshold_uncertainty_score":0.0052858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669664886282281,"score_gpt":0.3091324300475784,"score_spread":0.2924357811847556,"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."}}