{"id":"W3141036310","doi":"10.1016/j.clae.2021.02.008","title":"BCLA CLEAR - Evidence-based contact lens practice","year":2021,"lang":"en","type":"article","venue":"Contact Lens and Anterior Eye","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Alcon; CooperVision; British Comparative Literature Association","keywords":"Contact lens; Grading (engineering); Lens (geology); Optometry; Modality (human–computer interaction); Medicine; Eye care; Adaptation (eye); Medical physics; Computer science; Psychology; Ophthalmology; Engineering; Artificial intelligence","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":[0.03074003,0.0004879494,0.0008641705,0.003179524,0.001918559,0.006298829,0.002579763,0.006322025,0.05440793],"category_scores_gemma":[0.1506552,0.0005741135,0.001478779,0.002096441,0.001987261,0.003822508,0.006016243,0.005508989,0.01359353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006057407,"about_ca_system_score_gemma":0.03328856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004802899,"about_ca_topic_score_gemma":0.01212505,"domain_scores_codex":[0.9610798,0.01760742,0.006097056,0.001845382,0.01202656,0.001343731],"domain_scores_gemma":[0.7993927,0.0678118,0.025224,0.01274443,0.07137641,0.02345061],"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":[0.0007447078,0.0007506381,0.005278141,0.008926405,0.0002764641,0.0002713064,0.0003350129,0.0002755389,0.0007975757,0.01795788,0.4525276,0.5118586],"study_design_scores_gemma":[0.002043854,0.0007522401,0.02441792,0.04076605,0.0003038209,0.001259236,0.0007440532,0.0006828395,0.0009949151,0.02281987,0.9050902,0.0001249464],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01619074,0.1314061,0.01854067,0.4257579,0.0156572,0.002928213,0.004982919,0.001148657,0.3833876],"genre_scores_gemma":[0.4178419,0.09576944,0.1226252,0.2574624,0.01263013,0.005312605,0.01109919,0.0006976515,0.07656151],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05440793,"threshold_uncertainty_score":0.1820126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0341808880826926,"score_gpt":0.3031319929767309,"score_spread":0.2689511048940383,"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."}}