{"id":"W2008536450","doi":"10.1016/s1350-4533(00)00078-3","title":"Clinical decision-support systems for intensive care units using case-based reasoning","year":2000,"lang":"en","type":"article","venue":"Medical Engineering & Physics","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"Medical Research Council","keywords":"Intensive care; Medicine; Matching (statistics); Neonatal intensive care unit; Work (physics); Decision support system; Intensive care unit; Medical emergency; Expert system; Intensive care medicine; Computer science; Artificial intelligence; Pediatrics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007639431,0.0002359004,0.0003883798,0.0000542274,0.0001815995,0.0001195261,0.0005474124,0.0002049629,0.00001918419],"category_scores_gemma":[0.001265014,0.0002244328,0.000127911,0.0004768625,0.00004261646,0.0001754894,0.00007313793,0.0004753394,0.00001727616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007439596,"about_ca_system_score_gemma":0.000499375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007029014,"about_ca_topic_score_gemma":9.668142e-7,"domain_scores_codex":[0.9979632,0.00005608717,0.0005250951,0.0004566238,0.0005235233,0.0004754579],"domain_scores_gemma":[0.9970824,0.001410453,0.00008805901,0.0004825765,0.0005482667,0.0003882697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002037605,0.00002171779,0.0003561439,0.0001911664,0.00004689717,0.001185577,0.001130425,0.7502148,0.000006638557,0.001834096,0.001510771,0.2434815],"study_design_scores_gemma":[0.0005987128,0.0001266091,0.00001503315,0.0007994454,0.00002322988,0.0002808046,0.0001096772,0.9865616,0.00003153096,0.00003177345,0.01115363,0.0002679641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04660109,0.0004248679,0.9512759,0.0000615379,0.001030742,0.0002031363,0.0000143992,0.000330114,0.00005825247],"genre_scores_gemma":[0.8665203,0.000012916,0.1317761,0.0006553394,0.0008806483,0.00002996819,0.00003968436,0.00005157846,0.00003345592],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8199192,"threshold_uncertainty_score":0.9152104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03309167810542692,"score_gpt":0.3006811901368823,"score_spread":0.2675895120314554,"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."}}