{"id":"W4317749998","doi":"10.1093/jamia/ocad002","title":"MIMIC-IV on FHIR: converting a decade of in-patient data into an exchangeable, interoperable format","year":2023,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"Hospital for Sick Children","keywords":"Interoperability; Data format; Computer science; Patient data; World Wide Web; Database; Computer hardware","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.009337399,0.001039605,0.0005757586,0.002587347,0.0006852853,0.004296346,0.00309953,0.001002224,0.01181346],"category_scores_gemma":[0.03254,0.0009048005,0.001747522,0.003030211,0.0006475646,0.004849849,0.004587941,0.00184172,0.01127996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002713573,"about_ca_system_score_gemma":0.005626737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01518393,"about_ca_topic_score_gemma":0.01615951,"domain_scores_codex":[0.9943419,0.001719623,0.0009134984,0.001083355,0.001597656,0.0003440594],"domain_scores_gemma":[0.9869072,0.003151775,0.0007458604,0.006327208,0.002362059,0.0005058749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001432885,0.0003230737,0.02695607,0.001464442,0.0003735153,0.0007220965,0.001627637,0.03849955,0.00810149,0.06179877,0.6421875,0.216513],"study_design_scores_gemma":[0.0003197399,0.0003842412,0.01450815,0.001035369,0.0001379269,0.0007891557,0.001176466,0.09521709,0.02137132,0.03945696,0.8253362,0.0002673823],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03145755,0.0008322913,0.4240189,0.008304917,0.001285444,0.002736727,0.3528714,0.1323882,0.04610457],"genre_scores_gemma":[0.1292602,0.0009525525,0.3470458,0.002632851,0.0002191586,0.001288665,0.501227,0.00828865,0.009085088],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01518393,"threshold_uncertainty_score":0.04938143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04824375118723655,"score_gpt":0.3648114203584823,"score_spread":0.3165676691712457,"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."}}