{"id":"W4408295590","doi":"10.1038/s41433-025-03741-1","title":"Implantable collamer lens sizing optimization based on the anterion AS-OCT biometric parameters","year":2025,"lang":"en","type":"article","venue":"Eye","topic":"Corneal surgery and disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biometrics; Sizing; Optometry; Medicine; Ophthalmology; Computer science; Phakic intraocular lens; Lens (geology); Artificial intelligence; Optics; Eye disease; Refractive error; Physics","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":[0.0001897873,0.0006561442,0.0002700151,0.0005935328,0.0001712982,0.0008695169,0.000234426,0.0002828308,0.002136939],"category_scores_gemma":[0.0006352679,0.0002031839,0.0003219637,0.0003420271,0.000153167,0.0005113973,0.0002703637,0.0002273384,0.0005521402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000320783,"about_ca_system_score_gemma":0.0006426224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0015468,"about_ca_topic_score_gemma":0.003644496,"domain_scores_codex":[0.9997908,0.00002269131,0.00001388781,0.00003874371,0.0001092846,0.00002445139],"domain_scores_gemma":[0.9996951,0.00007336515,0.0000650901,0.00002549928,0.0001260229,0.00001500659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006621976,0.0001635163,0.01749301,0.0003611259,0.000121855,0.0004278518,0.000188899,0.1101187,0.5252044,0.002859675,0.005142813,0.3372559],"study_design_scores_gemma":[0.00005541207,0.0004161962,0.02925024,0.00003610243,0.0002161889,0.001229221,0.0002612821,0.7643914,0.1947499,0.001750361,0.007541246,0.000102368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5469602,0.001135833,0.4358946,0.0002930126,0.0001430237,0.0000887323,0.0004974216,0.00127362,0.01371356],"genre_scores_gemma":[0.9129449,0.000288554,0.08283045,0.00006144602,0.00002049042,0.00003371919,0.0002247726,0.0001645782,0.00343118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002136939,"threshold_uncertainty_score":0.007148802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918806422149838,"score_gpt":0.277781327259891,"score_spread":0.2585932630383926,"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."}}