{"id":"W4414825253","doi":"10.1016/j.ajo.2025.09.051","title":"RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study","year":2025,"lang":"en","type":"article","venue":"American Journal of Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; National Eye Institute; Canada Foundation for Innovation; Research to Prevent Blindness","keywords":"Longitudinal study; Glaucoma; Fundus (uterus); Longitudinal data; Fundus photography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001559769,0.0002163054,0.0008202475,0.001326971,0.0002214318,0.00004346768,0.0003293585,0.00003056839,0.00006792683],"category_scores_gemma":[0.0004784282,0.0001437264,0.0001578094,0.001546131,0.0001244241,0.00003735156,0.00003260282,0.0007943723,0.0000067885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003613448,"about_ca_system_score_gemma":0.0005474459,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3157156,"about_ca_topic_score_gemma":0.03320868,"domain_scores_codex":[0.9975696,0.0007155726,0.0006671306,0.0002990024,0.0003984898,0.0003502507],"domain_scores_gemma":[0.9983601,0.0004133209,0.0003437513,0.0004070686,0.0002344171,0.0002413477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003099716,0.0007758038,0.9894128,0.000005978813,0.0003109465,0.005184757,0.000560749,0.001579749,0.000007574341,0.000008934672,0.00002634978,0.001816343],"study_design_scores_gemma":[0.001170075,0.003065276,0.9903039,0.0001026357,0.0004276165,0.001791226,0.002534083,0.0004501715,0.000002353283,0.00002085402,0.00001910681,0.0001127547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890159,0.00008003705,0.00008171345,0.00909692,0.0001723246,0.000478623,0.000003378167,0.000006481165,0.001064666],"genre_scores_gemma":[0.9986517,7.921571e-7,0.0001508846,0.0009381542,0.00006584297,0.00001587906,0.000004515711,0.00001781829,0.0001544226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2825069,"threshold_uncertainty_score":0.9844328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827610480036402,"score_gpt":0.3715879706756423,"score_spread":0.3433118658752783,"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."}}