{"id":"W4395055042","doi":"10.1109/aimhc59811.2024.00021","title":"Extending Machine Learning-Based Early Sepsis Detection to Different Demographics","year":2024,"lang":"en","type":"article","venue":"","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Demographics; Computer science; Machine learning; Sepsis; Artificial intelligence; Medicine; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003991387,0.00134575,0.001375036,0.002863019,0.000491912,0.001219915,0.0009357468,0.0007768587,0.0008547764],"category_scores_gemma":[0.007534319,0.0001647737,0.001125828,0.00161514,0.0002300393,0.001488346,0.001285187,0.001378757,0.0008110799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005033615,"about_ca_system_score_gemma":0.001204869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005371847,"about_ca_topic_score_gemma":0.008325698,"domain_scores_codex":[0.9984645,0.0006010861,0.0001127333,0.0003854117,0.0002332257,0.0002032214],"domain_scores_gemma":[0.9972813,0.001190468,0.0002876469,0.00038527,0.0006332727,0.0002219429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009640279,0.00123074,0.4458095,0.0003313421,0.0008474434,0.0003040717,0.000143683,0.1013135,0.003297698,0.0008644239,0.02597021,0.4189233],"study_design_scores_gemma":[0.0001007979,0.0007412427,0.1168073,0.00020428,0.0004044636,0.0005241969,0.0005623945,0.857767,0.004231545,0.006451936,0.01211783,0.0000869928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7786062,0.01170882,0.1744886,0.006965941,0.001291562,0.0004945156,0.01337779,0.003256712,0.009809827],"genre_scores_gemma":[0.936462,0.001459344,0.04371905,0.001031234,0.0005366382,0.0001162603,0.0153611,0.00005749655,0.001256941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005371847,"threshold_uncertainty_score":0.02110869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04936383551564988,"score_gpt":0.3286236600113803,"score_spread":0.2792598244957304,"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."}}