{"id":"W7127082407","doi":"10.1051/bioconf/202519300028/pdf","title":"Unlocking Electronic Medical Record Success: Readiness Assessment with the DOQ-IT Method","year":2025,"lang":"en","type":"article","venue":"Springer Link (Chiba Institute of Technology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0105526,0.0004485133,0.000532155,0.003900362,0.0009309873,0.002006379,0.0007174344,0.0004315513,0.002615384],"category_scores_gemma":[0.02287325,0.000366261,0.001275092,0.002553082,0.0006482759,0.001853651,0.002198388,0.001034561,0.0004647087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001110329,"about_ca_system_score_gemma":0.002618308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002294322,"about_ca_topic_score_gemma":0.004628454,"domain_scores_codex":[0.9914625,0.004301741,0.001312269,0.0003878172,0.001928739,0.0006068643],"domain_scores_gemma":[0.984885,0.005882496,0.003437925,0.0008451469,0.004034395,0.0009151189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002821992,0.001552444,0.860646,0.0003023763,0.0001359985,0.00009812933,0.005811807,0.000411285,0.001023531,0.001102137,0.00135694,0.1272772],"study_design_scores_gemma":[0.0001567244,0.002492517,0.952511,0.0002750509,0.0001461936,0.0002111942,0.02683406,0.005764227,0.003379638,0.001154905,0.006952004,0.0001224698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813867,0.000106244,0.006444271,0.000698017,0.00004401934,0.002622409,0.0004147031,0.00006898124,0.008214624],"genre_scores_gemma":[0.9784949,0.0001667209,0.01584454,0.0001528188,0.00001692094,0.003168789,0.0005121087,0.0000188637,0.001624412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0105526,"threshold_uncertainty_score":0.05580813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356917455096694,"score_gpt":0.4030771848466604,"score_spread":0.3795080102956935,"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."}}