{"id":"W6912897239","doi":"10.5683/sp2/ca9uh7","title":"Activity data vs clinical data extraction from the EMR","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Data extraction; Electronic medical record; Extraction (chemistry); Data collection; Pattern recognition (psychology); Data quality","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":[0.004495015,0.002542876,0.001582765,0.003905528,0.0009615719,0.002889129,0.003463055,0.003128691,0.01539724],"category_scores_gemma":[0.02939666,0.0006429887,0.002526167,0.003982819,0.0009765262,0.002037142,0.002334693,0.00228272,0.02029456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002732199,"about_ca_system_score_gemma":0.003405353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04434458,"about_ca_topic_score_gemma":0.07377186,"domain_scores_codex":[0.9956716,0.001230799,0.000697252,0.001047365,0.0009100397,0.000442979],"domain_scores_gemma":[0.9906288,0.004367685,0.0008834059,0.002283844,0.001452474,0.0003836969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00085736,0.0002113793,0.01167035,0.00302205,0.0002953399,0.0001226193,0.0001116291,0.002193681,0.0005216234,0.001658355,0.9636732,0.01566229],"study_design_scores_gemma":[0.001850154,0.0002819485,0.03054887,0.002055736,0.0005738803,0.0007330713,0.0005468458,0.009981418,0.002893842,0.00778556,0.9425386,0.0002101599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002286788,0.0003505246,0.0006013236,0.000529992,0.0001085631,0.00006785127,0.9940619,0.000783372,0.00120971],"genre_scores_gemma":[0.003743292,0.0001170146,0.001403458,0.0001948961,0.00002354904,0.0001459518,0.9937295,0.0000619005,0.0005804913],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04434458,"threshold_uncertainty_score":0.08817291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2794447724494842,"score_gpt":0.4561373810933542,"score_spread":0.17669260864387,"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."}}