{"id":"W6910183189","doi":"10.3886/e108503v1-123140","title":"Optical Coherence Tomography Image Retinal Database","year":2019,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Optical coherence tomography; Retinal; Tomography; Coherence (philosophical gambling strategy); Image (mathematics); Image processing","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006603093,0.0005631736,0.0008426451,0.0002917791,0.00009532965,0.0001922365,0.002096659,0.0004901428,0.00105626],"category_scores_gemma":[0.003452726,0.0005060461,0.0001455159,0.0004300304,0.0003908974,0.0005096247,0.002774523,0.001499887,0.002144367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004716544,"about_ca_system_score_gemma":0.0002597771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007302455,"about_ca_topic_score_gemma":0.00002839016,"domain_scores_codex":[0.9963273,0.00005016751,0.0005448173,0.001420221,0.0009593347,0.0006981126],"domain_scores_gemma":[0.9922161,0.0005990636,0.0002719209,0.006228176,0.000147823,0.0005369398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002390109,0.0002257482,0.0003739121,0.0006794779,0.000113221,0.001067744,0.000003475265,1.130425e-7,0.0002418349,0.00002229368,0.9964384,0.0005946984],"study_design_scores_gemma":[0.001159649,0.000349653,0.000918117,0.001793189,0.000901373,0.0003781375,0.00001657849,0.00005701411,0.0002770701,0.00001234581,0.9935598,0.0005771107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003637674,0.0009545291,0.0001549395,0.0003560859,0.0005679166,0.000603509,0.9962407,0.0001178836,0.0006406223],"genre_scores_gemma":[0.0001893186,0.0007841894,0.008494334,0.001007852,0.0007210115,0.00002076341,0.9885752,0.00005204263,0.0001553332],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008339395,"threshold_uncertainty_score":0.9998569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05042015660842675,"score_gpt":0.326399492270317,"score_spread":0.2759793356618903,"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."}}