{"id":"W4404242870","doi":"10.12968/opti.2023.267.6901.21","title":"CPD: How clinical science translates into clinical practice","year":2023,"lang":"en","type":"article","venue":"Optician","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Clinical Practice; Computer science; Data science; Psychology; Medical physics; Medical education; Medicine; Family 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003908967,0.0001323355,0.0003986924,0.0001354056,0.0003286728,0.00003734861,0.0001660909,0.0001612705,0.00003836333],"category_scores_gemma":[0.005953121,0.0001050971,0.0001552256,0.0007481874,0.00135954,0.0002803158,0.0001041808,0.0004517219,0.0007475021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002170047,"about_ca_system_score_gemma":0.0002298683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218063,"about_ca_topic_score_gemma":0.000002206876,"domain_scores_codex":[0.9982171,0.0001394289,0.0004356832,0.0004429634,0.0003460693,0.0004187368],"domain_scores_gemma":[0.9979612,0.001165519,0.0001019259,0.000308497,0.0002059197,0.0002569961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001101187,0.003087468,0.8736206,0.0001517042,0.0005187279,0.001469065,0.00211198,0.000001892835,0.0006710787,0.002738007,0.02495166,0.08957662],"study_design_scores_gemma":[0.002201316,0.006853758,0.917696,0.0001204428,0.0003982368,0.0001846955,0.003053101,0.00075179,0.0001713462,0.0004612419,0.06785524,0.0002528302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309124,0.000162181,0.00004198205,0.05294154,0.001446044,0.0002855379,0.00000142659,0.0001845433,0.01402434],"genre_scores_gemma":[0.9898476,0.0003741443,0.005021619,0.00214206,0.0005983196,0.00001176256,0.000005345736,0.00001553891,0.001983582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08932379,"threshold_uncertainty_score":0.9607877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486111338846161,"score_gpt":0.5413134279829269,"score_spread":0.3927022940983108,"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."}}