{"id":"W4387798706","doi":"10.1111/trf.17585","title":"An unsupervised learning approach to identify immunoglobulin utilization patterns using electronic health records","year":2023,"lang":"en","type":"article","venue":"Transfusion","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre; Canadian Blood Services; Health Sciences Centre; Ontario Stroke Network; Sunnybrook Health Science Centre; University of Toronto; Queen's University; McMaster University; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Blood Services; Calgary Foundation","keywords":"Medicine; Economic shortage; Cluster (spacecraft); Demographics; Health records; Cluster analysis; Electronic health record; Emergency medicine; Health care; Demography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002754394,0.001137264,0.00101208,0.006247905,0.000965871,0.001988129,0.001842662,0.001219552,0.001654326],"category_scores_gemma":[0.00872519,0.0004493266,0.001867778,0.004406652,0.0005827898,0.001129538,0.001356094,0.00146384,0.001013372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259503,"about_ca_system_score_gemma":0.002719476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01760812,"about_ca_topic_score_gemma":0.01674805,"domain_scores_codex":[0.9975824,0.0007077929,0.0002896251,0.0008269431,0.0003015763,0.0002916518],"domain_scores_gemma":[0.9952678,0.002826341,0.0005786691,0.0003666737,0.0007783838,0.0001820365],"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":[0.0009463259,0.002654833,0.3406709,0.0005839605,0.001342486,0.0009282853,0.001785492,0.08598036,0.004519608,0.004106408,0.02289171,0.5335895],"study_design_scores_gemma":[0.00006151441,0.0001379508,0.04131753,0.00009275891,0.0001629694,0.0002345741,0.0008007891,0.9450728,0.001386999,0.006479591,0.00419789,0.00005469963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4374442,0.001296953,0.5294165,0.002481399,0.0003037647,0.001915577,0.01568403,0.005559152,0.005898378],"genre_scores_gemma":[0.7360922,0.0004153048,0.2414189,0.0003556916,0.0002356227,0.001142136,0.01785128,0.0001283734,0.002360496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01760812,"threshold_uncertainty_score":0.03501123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06471953312103576,"score_gpt":0.3312545889771531,"score_spread":0.2665350558561174,"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."}}