{"id":"W2111093770","doi":"10.1109/iri.2012.6303060","title":"Electronic medical referral system: Decision support and recommendation approach","year":2012,"lang":"en","type":"article","venue":"","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Referral; Decision support system; Process (computing); Domain (mathematical analysis); Computer science; Clinical decision support system; Medicine; Family medicine; Medical emergency; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003056556,0.0007483691,0.001745558,0.003246149,0.001195767,0.003510354,0.003346706,0.003864294,0.005876939],"category_scores_gemma":[0.006488075,0.0004851237,0.0009325511,0.004504235,0.0004269142,0.002660514,0.0008733727,0.001137876,0.003063473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001612475,"about_ca_system_score_gemma":0.001689039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01733999,"about_ca_topic_score_gemma":0.01911509,"domain_scores_codex":[0.9968346,0.001029335,0.0004504001,0.0005657316,0.0009204158,0.0001995627],"domain_scores_gemma":[0.9964085,0.001668177,0.0002346848,0.0002684075,0.001207472,0.0002125979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009113474,0.001835163,0.01234697,0.000925135,0.0005114508,0.001231492,0.0004250172,0.1031421,0.008554401,0.01933529,0.02687946,0.8239022],"study_design_scores_gemma":[0.0001737914,0.0001884082,0.002178328,0.0001111924,0.0001423342,0.0003507533,0.0002893296,0.962518,0.004072253,0.01299272,0.01690105,0.0000819679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04905089,0.002301961,0.9096571,0.006296222,0.000284144,0.002115329,0.002831216,0.008740542,0.01872264],"genre_scores_gemma":[0.3767704,0.001166937,0.6091427,0.001214973,0.0003294281,0.0005009117,0.002401452,0.00008729043,0.008385969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01733999,"threshold_uncertainty_score":0.03447813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856517604298033,"score_gpt":0.2780469398102521,"score_spread":0.2494817637672717,"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."}}