{"id":"W4321604926","doi":"10.2196/preprints.46749","title":"A Call for Standardization of Clinical Content for EMRs in Primary Care across Canada (Preprint)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Standardization; Preprint; Primary care; Consistency (knowledge bases); Medical record; Medicine; Library science; Family medicine; Computer science; World Wide Web; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001731871,0.0001586602,0.0005679989,0.00006035276,0.00006454394,0.000198282,0.001413791,0.0001852315,0.000001583363],"category_scores_gemma":[0.0002508102,0.000135358,0.0002068191,0.0002196886,0.00004175557,0.0008457052,0.001125964,0.0001573822,0.000001744721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002587213,"about_ca_system_score_gemma":0.003501445,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08732966,"about_ca_topic_score_gemma":0.167128,"domain_scores_codex":[0.9970012,0.00005599564,0.001614988,0.0005307437,0.0004918172,0.0003052987],"domain_scores_gemma":[0.9976029,0.0003777876,0.0005962923,0.0007251845,0.0005992528,0.00009856378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005257886,0.0002043583,0.2868322,0.01693833,0.0003118767,0.00001319065,0.07236372,0.2032653,0.00006185619,0.02397171,0.122791,0.2727207],"study_design_scores_gemma":[0.007249069,0.0006988087,0.2542787,0.001839495,0.00001193962,0.00000413644,0.01771169,0.5692751,0.003567139,0.002632229,0.1409896,0.001742177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03821051,0.00003361893,0.953897,0.0006984528,0.003055624,0.002530843,0.0006918665,0.00009009997,0.0007919784],"genre_scores_gemma":[0.9456612,0.00003885471,0.04932749,0.001514988,0.0001907212,0.0008295388,0.0006155597,0.0000231218,0.001798475],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9074507,"threshold_uncertainty_score":0.9187479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1353219287410736,"score_gpt":0.3591620592005005,"score_spread":0.223840130459427,"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."}}