{"id":"W3206674812","doi":"","title":"Osteoporosis guideline implementation in family medicine using electronic medical records : Survey of learning needs and barriers Application des lignes directrices sur l’ostéoporose en médecine familiale à l’aide des dossiers médicaux électroniquesApplication des lignes directrices sur l’ostéoporose en médecine familiale à l’aide des dossiers médicaux électroniques","year":2016,"lang":"fr","type":"article","venue":"Canadian Family Physician","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Guideline; Medicine; Gynecology; Family medicine; Library science; Computer science; Pathology","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":[0.008005398,0.0001726784,0.0005023391,0.001895855,0.002181696,0.001716365,0.001147381,0.0009721877,0.002529116],"category_scores_gemma":[0.05478973,0.0005751725,0.0007279651,0.003731541,0.0005959319,0.001507568,0.001483085,0.001480603,0.0001658407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01235889,"about_ca_system_score_gemma":0.04635435,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7077223,"about_ca_topic_score_gemma":0.7878348,"domain_scores_codex":[0.9890327,0.002436507,0.001865918,0.0004733881,0.004927404,0.001264039],"domain_scores_gemma":[0.9535571,0.01533922,0.01275884,0.0009443011,0.0118034,0.005597088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005108137,0.0004514992,0.9268062,0.0003925045,0.0001154056,0.0001866984,0.01771698,0.00009190201,0.0001669075,0.0001809814,0.004489705,0.04935008],"study_design_scores_gemma":[0.00002555807,0.0000975908,0.9793215,0.0005374415,0.00004608602,0.0001489261,0.01390967,0.0002745242,0.0001021333,0.00003951031,0.005464941,0.0000319199],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759651,0.002065382,0.0002612637,0.01137844,0.00006835474,0.0004092909,0.001488675,0.00002147745,0.008341854],"genre_scores_gemma":[0.9893938,0.002753911,0.002774986,0.002452345,0.00004095633,0.0002407144,0.0009107492,0.0000132621,0.00141929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2922777,"threshold_uncertainty_score":0.5879979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06837590731167736,"score_gpt":0.3748281107413171,"score_spread":0.3064522034296397,"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."}}