{"id":"W4409529414","doi":"10.2196/66223","title":"Leveraging Electronic Health Records in International Humanitarian Clinics for Population Health Research: Cross-Sectional Study","year":2025,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Clair College","funders":"","keywords":"Concordance; Public health; Medical classification; Documentation; Family medicine; Cross-sectional study; Population; Medicine; Medical record; Test (biology); Diagnosis code; Terminology; Medical emergency; Psychology; Nursing; Computer science; Environmental health; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01216499,0.0003850967,0.0004719298,0.003311239,0.0009795929,0.001983057,0.001021387,0.0009203421,0.001469001],"category_scores_gemma":[0.03236568,0.0008387751,0.0006352009,0.005206018,0.0006656208,0.002219862,0.002163903,0.001280684,0.0004574423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009448,"about_ca_system_score_gemma":0.001524761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006800433,"about_ca_topic_score_gemma":0.01021198,"domain_scores_codex":[0.9850867,0.007416829,0.002329624,0.001778327,0.00251201,0.0008766142],"domain_scores_gemma":[0.960224,0.01280763,0.01956939,0.003219099,0.003022801,0.001157136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002285668,0.00009144162,0.9982304,0.00003094125,0.0000306882,0.00002710966,0.0004304778,0.00001060775,0.00002860938,0.00002493632,0.0001574759,0.0009145563],"study_design_scores_gemma":[0.00001764816,0.0002052369,0.9956956,0.00009954552,0.00005402094,0.000258328,0.002500202,0.0002907251,0.00007613227,0.00002704172,0.0007654557,0.00001011028],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953027,0.0005194785,0.0007045428,0.0001932123,0.00002096903,0.0003804542,0.001772868,0.000009243816,0.001096516],"genre_scores_gemma":[0.9961711,0.000310236,0.001164744,0.0003349333,0.00004572007,0.0005119602,0.001312293,0.000007812769,0.0001411981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01216499,"threshold_uncertainty_score":0.06433541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431953505405493,"score_gpt":0.4806827429693594,"score_spread":0.3374873924288101,"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."}}