{"id":"W6976805290","doi":"10.60692/k0b81-9m621","title":"AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Glaucoma; Fundus (uterus); Receiver operating characteristic; Set (abstract data type); Expert system; Medical screening","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":[0.005562772,0.001404247,0.001205916,0.00191529,0.0008120253,0.001701841,0.001897285,0.002272323,0.002595758],"category_scores_gemma":[0.01577396,0.0002956069,0.001154663,0.001184778,0.0006530181,0.001377991,0.002257197,0.001971457,0.001330525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00163379,"about_ca_system_score_gemma":0.00313614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01078694,"about_ca_topic_score_gemma":0.009204241,"domain_scores_codex":[0.9963011,0.001092412,0.0003276423,0.0007588061,0.00127868,0.000241381],"domain_scores_gemma":[0.9933171,0.003214948,0.0004415925,0.0009640232,0.001616627,0.0004457026],"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":[0.0008689317,0.001399188,0.02379189,0.001589571,0.000738545,0.000743416,0.000322385,0.1661616,0.009308427,0.006124637,0.2669626,0.5219889],"study_design_scores_gemma":[0.0003503916,0.0005831664,0.01422815,0.0002172115,0.0001384225,0.0006537648,0.0003267183,0.8963924,0.01260261,0.01428797,0.06012474,0.00009438291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4671478,0.01727109,0.3592325,0.02837422,0.0039417,0.0031093,0.04352196,0.03909976,0.0383017],"genre_scores_gemma":[0.5721784,0.001867178,0.3496788,0.003272251,0.0006627729,0.0009413795,0.06326792,0.0008200692,0.007311197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01078694,"threshold_uncertainty_score":0.02941906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0916754857433784,"score_gpt":0.2793529713754244,"score_spread":0.1876774856320459,"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."}}