{"id":"W4407760181","doi":"10.1016/j.jcjo.2025.01.020","title":"Accuracy of 7 artificial intelligence-based intraocular lens power calculation formulas in medium-long eyes: 2-center study","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Ophthalmology","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Center (category theory); Optometry; Lens (geology); Power (physics); Optics; Computer science; Artificial intelligence; Ophthalmology; Physics; Medicine; Chemistry","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":[0.002559539,0.000690424,0.0007761553,0.0009862159,0.0006087036,0.001089408,0.0009186596,0.0006601042,0.001025819],"category_scores_gemma":[0.01034821,0.0003725533,0.001087352,0.0008986951,0.000643593,0.001287851,0.0008451666,0.0008107913,0.0004343917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054415,"about_ca_system_score_gemma":0.0006540826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006374455,"about_ca_topic_score_gemma":0.005500454,"domain_scores_codex":[0.9978272,0.0006774335,0.0002801826,0.0004953764,0.0006030248,0.000116721],"domain_scores_gemma":[0.9893636,0.0041222,0.002412711,0.001087209,0.002568335,0.0004460531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005149012,0.0008816781,0.9695173,0.00006398693,0.0004639845,0.0001520364,0.0006896409,0.0007196877,0.0008458089,0.00008867193,0.0003031248,0.02112504],"study_design_scores_gemma":[0.0003038188,0.003986718,0.9857762,0.00003099833,0.0003825323,0.0004909137,0.001006332,0.00591306,0.001389281,0.0001251739,0.000529082,0.00006583551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999138,0.0001832204,0.0002745082,0.00001258526,0.000008260672,0.0000150223,0.0001102808,0.000009345983,0.0002486755],"genre_scores_gemma":[0.9990391,0.00007560807,0.0004471305,0.00001862244,0.000007536313,0.0000164581,0.0002437181,0.000008389055,0.0001434807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006374455,"threshold_uncertainty_score":0.01353633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05344786943727463,"score_gpt":0.3783648017458696,"score_spread":0.3249169323085949,"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."}}