{"id":"W4414159671","doi":"10.1097/icu.0000000000001173","title":"Accelerating insight: the role of artificial intelligence in health economic analysis for ophthalmology","year":2025,"lang":"en","type":"article","venue":"Current Opinion in Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Automation; Economic analysis; Health technology; MEDLINE; Applications of artificial intelligence; Precision medicine","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":[0.07387128,0.001542078,0.004450684,0.00738317,0.0007105766,0.00909126,0.002216041,0.004335588,0.007761256],"category_scores_gemma":[0.314052,0.0008208636,0.006022032,0.006365549,0.002822719,0.007160185,0.003147466,0.006984266,0.00111574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006273546,"about_ca_system_score_gemma":0.02004086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003580708,"about_ca_topic_score_gemma":0.004072968,"domain_scores_codex":[0.9258217,0.05600172,0.006874251,0.001738474,0.008842827,0.0007210621],"domain_scores_gemma":[0.475054,0.4777373,0.01691803,0.005470159,0.02324025,0.001580219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004359338,0.00006021486,0.001686663,0.2273712,0.006929849,0.0002552637,0.0004563548,0.007298197,0.000221574,0.09642321,0.0644269,0.5944347],"study_design_scores_gemma":[0.0003652728,0.000354419,0.003635854,0.4327573,0.01024875,0.0005578251,0.0004642831,0.007979861,0.0005775078,0.2245341,0.3182812,0.0002436674],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.0003782528,0.9542711,0.008095499,0.03201342,0.002410244,0.0002335394,0.0002642028,0.00009167406,0.002241994],"genre_scores_gemma":[0.02396054,0.9323458,0.02034412,0.01656904,0.004878594,0.0008260314,0.0002725832,0.00007869751,0.000724637],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.07387128,"threshold_uncertainty_score":0.3906733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109562993888311,"score_gpt":0.4386335636630146,"score_spread":0.3290705697747037,"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."}}