{"id":"W2984801351","doi":"","title":"Data quality in electronic medical records in Manitoba: Do problem lists reflect chronic disease as defined by prescriptions?","year":2017,"lang":"en","type":"article","venue":"PubMed","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Manitoba Health; McMaster University Medical Centre; University of Manitoba","funders":"","keywords":"Medicine; Medical prescription; Medical record; Documentation; Remuneration; Family medicine; Quality management; Service (business); Computer science; Nursing; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01437249,0.0003942385,0.0008162985,0.0002664228,0.0009971184,0.0000935759,0.002721872,0.0005991828,0.0003052511],"category_scores_gemma":[0.009799179,0.0003793037,0.00007264187,0.0003626713,0.0001577156,0.000796063,0.0009820029,0.003095899,0.0003016298],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.006559501,"about_ca_system_score_gemma":0.008571957,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05567918,"about_ca_topic_score_gemma":0.5499787,"domain_scores_codex":[0.9883768,0.003589461,0.002101203,0.001333542,0.001038026,0.003560982],"domain_scores_gemma":[0.9932584,0.0009113415,0.000935076,0.003661626,0.0001134585,0.001120123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000933319,0.0009712556,0.7099456,0.003118773,0.00007531141,0.00009604058,0.0004009005,0.000001465142,0.00001923129,0.009093733,0.1307335,0.1446109],"study_design_scores_gemma":[0.003741655,0.000089901,0.7058427,0.0006328972,0.00001991969,0.000005142798,0.0001178824,0.0002534873,0.00000205632,0.00515368,0.283695,0.0004456245],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.884721,0.01645702,0.00008437722,0.05254822,0.003115809,0.01661622,0.0005377552,0.0004188765,0.02550076],"genre_scores_gemma":[0.9739879,0.002561907,0.00003735916,0.001099764,0.0009174397,0.01689969,0.0004097551,0.0000910559,0.00399512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4942996,"threshold_uncertainty_score":0.9998659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1751192935811779,"score_gpt":0.4707822445511964,"score_spread":0.2956629509700185,"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."}}