{"id":"W4409640280","doi":"10.2196/71777","title":"Advancing Emergency Care With Digital Twins","year":2025,"lang":"en","type":"editorial","venue":"JMIR Aging","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; Wearable computer; Data science; Computer science; Predictive analytics; Paradigm shift; Wearable technology; Big data; Corporate governance; Knowledge management; Business; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01221747,0.0025133,0.002519742,0.003405638,0.003432105,0.01303032,0.003765858,0.02193905,0.0135225],"category_scores_gemma":[0.0566547,0.00110542,0.003027343,0.001551096,0.004143669,0.008224632,0.004512354,0.03479519,0.007294638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003622561,"about_ca_system_score_gemma":0.004695002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001817419,"about_ca_topic_score_gemma":0.004264398,"domain_scores_codex":[0.9917169,0.002327506,0.001207162,0.0007179583,0.003593141,0.0004373732],"domain_scores_gemma":[0.9534177,0.03183372,0.001617811,0.001160109,0.007559096,0.00441171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001808204,0.0000107669,0.00003018957,0.0004647632,0.00002241052,0.0001003024,0.00007235003,0.00003669719,0.00003543778,0.001304095,0.985231,0.01267396],"study_design_scores_gemma":[0.00002430003,0.00001546259,0.00009315294,0.0009689502,0.00003711115,0.0001482921,0.000097561,0.00007677672,0.00005256665,0.001703873,0.9967688,0.00001314531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0000309007,0.01404185,0.0002182798,0.0747072,0.9094002,0.0000165071,0.00003203102,0.00004848903,0.00150454],"genre_scores_gemma":[0.0004207702,0.01179294,0.0001612893,0.03591019,0.9481586,0.00002119545,0.0000175294,0.0000293326,0.003488266],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02193905,"threshold_uncertainty_score":0.06461287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02896911213518309,"score_gpt":0.4076225008403718,"score_spread":0.3786533887051887,"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."}}