{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001407133,0.000149928,0.000200063,0.0002051622,0.0001361104,0.00002300343,0.00008870607,0.00005888881,0.001382223],"category_scores_gemma":[0.00003292949,0.0001199493,0.0002208818,0.0005703224,0.0002005986,0.00005867779,0.000001432248,0.0003457417,0.0007767527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000335353,"about_ca_system_score_gemma":0.0001050887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002577807,"about_ca_topic_score_gemma":0.000002251538,"domain_scores_codex":[0.9983237,0.00003050189,0.0002096785,0.0002958479,0.0007868572,0.0003534079],"domain_scores_gemma":[0.998961,0.0001380055,0.00002124982,0.0002134945,0.00004912337,0.0006171152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008211411,0.001995767,0.02733714,0.0002276691,0.0004020816,0.007293264,0.0001767112,0.000090585,0.002010497,0.000168198,0.005407685,0.9540693],"study_design_scores_gemma":[0.03103456,0.003500924,0.7102151,0.007134558,0.004463184,0.005138788,0.002854912,0.1571594,0.05382356,0.002519442,0.01922778,0.00292782],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7325054,0.0002668664,0.2325287,0.01824591,0.001388562,0.0007382459,0.00005122135,0.001327745,0.01294737],"genre_scores_gemma":[0.9977955,0.0001153005,0.0003318899,0.0009971929,0.00008022394,0.00005742595,0.00001291242,0.00002281732,0.0005867848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9511414,"threshold_uncertainty_score":0.9995307,"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."}}