{"id":"W4399891662","doi":"10.18280/ria.380330","title":"Automated Screening System for Grading of Retinal Abnormalities","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retinal; Grading (engineering); Optometry; Computer science; Ophthalmology; Medicine; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052246,0.0005777346,0.0008105465,0.003968485,0.0004343768,0.0009309735,0.0009834307,0.0006720357,0.003256029],"category_scores_gemma":[0.001837024,0.0002437887,0.0004429519,0.001189667,0.0001786741,0.0006201545,0.0005926693,0.000376021,0.002140961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004707681,"about_ca_system_score_gemma":0.0007227186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003055694,"about_ca_topic_score_gemma":0.002843782,"domain_scores_codex":[0.9988477,0.0001616386,0.0001318303,0.0002773695,0.0005067543,0.00007462204],"domain_scores_gemma":[0.9984516,0.0001876182,0.0001557194,0.0002000651,0.0009376824,0.0000673087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001119236,0.0003714722,0.0201912,0.0004730981,0.000146111,0.0003737403,0.0001279158,0.00493973,0.1418761,0.00149865,0.02837637,0.8005063],"study_design_scores_gemma":[0.0003450694,0.001338322,0.1109401,0.0002177299,0.0004807418,0.003907428,0.0002202384,0.5252883,0.3033164,0.002883169,0.05073269,0.0003298371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1723434,0.001927356,0.77021,0.0003202735,0.0003267922,0.001758656,0.006147448,0.0383767,0.008589281],"genre_scores_gemma":[0.483932,0.001159354,0.4942701,0.0002961587,0.0001775002,0.0009086653,0.009759681,0.0003397773,0.009156816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003968485,"threshold_uncertainty_score":0.01089251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04855820034048513,"score_gpt":0.3249544785334105,"score_spread":0.2763962781929253,"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."}}