{"id":"W4324020214","doi":"10.1111/ctr.14961","title":"Utilization of machine learning to model the effect of blood product transfusion on short‐term lung transplant outcomes","year":2023,"lang":"en","type":"article","venue":"Clinical Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Alexandra Hospital; University of Alberta","funders":"","keywords":"Medicine; Perioperative; Blood product; Blood transfusion; Fresh frozen plasma; Renal replacement therapy; Cryoprecipitate; Mechanical ventilation; Surgery; Anesthesia; Internal medicine; Platelet","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":[0.003263113,0.0009070254,0.0005297248,0.0008686843,0.0001825058,0.0008220636,0.000451543,0.0005001942,0.0008575741],"category_scores_gemma":[0.005941533,0.0002618049,0.0005268049,0.0003765043,0.0002337081,0.0005008646,0.0003523408,0.000843428,0.0001671935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004796471,"about_ca_system_score_gemma":0.000950471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005959236,"about_ca_topic_score_gemma":0.004312107,"domain_scores_codex":[0.999505,0.0002945347,0.00002825704,0.00006136367,0.00005009852,0.00006076085],"domain_scores_gemma":[0.9954334,0.0039352,0.0002824185,0.00009821974,0.0001744772,0.00007630904],"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":[0.0006856053,0.0007216248,0.1956874,0.00005550223,0.0005657913,0.0001428143,0.00004335411,0.7553871,0.0006318004,0.0004822492,0.0004855705,0.04511129],"study_design_scores_gemma":[0.00001091476,0.0001438884,0.00645254,0.0000082668,0.00004207369,0.00002625578,0.000008770521,0.9927264,0.0001758276,0.0003196812,0.00007981299,0.00000560288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9439501,0.0008479102,0.05297893,0.0005514111,0.00007243012,0.00005744581,0.0003458952,0.0001741237,0.001021703],"genre_scores_gemma":[0.9941964,0.0001791071,0.004831094,0.00004450699,0.00003150214,0.00003739966,0.0002199197,0.000007797401,0.0004522346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005959236,"threshold_uncertainty_score":0.01725721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09693528149483731,"score_gpt":0.4362474083633126,"score_spread":0.3393121268684753,"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."}}