{"id":"W4415785920","doi":"10.1051/bioconf/202519300028","title":"Unlocking Electronic Medical Record Success: Readiness Assessment with the DOQ-IT Method","year":2025,"lang":"fr","type":"article","venue":"BIO Web of Conferences","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vendor; Medical record; Electronic medical record; Work (physics); Quality (philosophy); Information technology; Quarter (Canadian coin); Medical information","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01134083,0.0005452873,0.001338218,0.0003442057,0.0008976773,0.00007305641,0.00152154,0.001113317,0.004357919],"category_scores_gemma":[0.0007258675,0.0003480422,0.0001616429,0.001528229,0.0006937399,0.0001960246,0.0002690776,0.003361458,0.00005646576],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009495863,"about_ca_system_score_gemma":0.10491,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01507487,"about_ca_topic_score_gemma":0.08702828,"domain_scores_codex":[0.986747,0.007027998,0.001939692,0.0008226787,0.00131981,0.002142772],"domain_scores_gemma":[0.9894058,0.007115235,0.001259535,0.0009237425,0.0009243303,0.0003713909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002360737,0.0002706433,0.1293365,0.003974726,0.0006331183,0.00001341321,0.0009163082,0.00000588394,0.00003585875,0.5072241,0.04126154,0.3160919],"study_design_scores_gemma":[0.001649919,0.0009241086,0.01033718,0.01075128,0.000303592,0.00001631067,0.00668934,0.006570547,0.0001444665,0.00300497,0.9591841,0.000424204],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05068755,0.03377511,0.08444911,0.5720143,0.008737735,0.004477325,0.00004477329,0.000196835,0.2456173],"genre_scores_gemma":[0.9596034,0.01017374,0.001219049,0.003343096,0.000775048,0.0004587096,0.00001659883,0.00004335616,0.024367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9179226,"threshold_uncertainty_score":0.9998972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04690402444216106,"score_gpt":0.4637762927106875,"score_spread":0.4168722682685265,"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."}}