{"id":"W4414085277","doi":"10.2196/67529","title":"Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public health; Health care; Diabetic retinopathy; Public healthcare; MEDLINE; Telemedicine; Retinopathy","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":[0.02200704,0.0007120425,0.0004966257,0.0008455902,0.000522484,0.001213289,0.001725826,0.001155507,0.0009691266],"category_scores_gemma":[0.03837255,0.0004135053,0.0006927763,0.0008655575,0.0008104286,0.0009433397,0.001218788,0.0008848711,0.0004011069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002890143,"about_ca_system_score_gemma":0.00217241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008984953,"about_ca_topic_score_gemma":0.006283548,"domain_scores_codex":[0.9875357,0.008909459,0.0007536875,0.00114426,0.001161736,0.0004952155],"domain_scores_gemma":[0.9543148,0.02409392,0.004838265,0.005292902,0.009663808,0.001796349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01221541,0.04576908,0.5794421,0.002008394,0.001449362,0.0008230848,0.005178142,0.05929623,0.008238408,0.001729234,0.00691397,0.2769365],"study_design_scores_gemma":[0.005574218,0.04864825,0.6188141,0.0005592158,0.0009373605,0.000994887,0.004869618,0.2936876,0.01452283,0.001303084,0.009789645,0.0002992593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905282,0.00009198557,0.005559635,0.0002019271,0.00002603969,0.001670839,0.0005171613,0.0002974883,0.001106598],"genre_scores_gemma":[0.97734,0.00007933261,0.01986361,0.0001848409,0.00001724893,0.001116976,0.001128465,0.0000172511,0.0002522356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02200704,"threshold_uncertainty_score":0.1163858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04360005069517863,"score_gpt":0.4312347729464273,"score_spread":0.3876347222512486,"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."}}