{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00202784,0.0002626004,0.0007844749,0.0002435916,0.0001165085,0.000008151023,0.0001522979,0.0001457637,0.00002301992],"category_scores_gemma":[0.0002044362,0.0001614904,0.0004192057,0.000558704,0.000102532,0.00007442926,0.000004842963,0.0003938904,0.000007624029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009361998,"about_ca_system_score_gemma":0.00004402144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002367022,"about_ca_topic_score_gemma":0.00003131981,"domain_scores_codex":[0.9971254,0.0005298631,0.001115242,0.000433205,0.000546316,0.0002499945],"domain_scores_gemma":[0.9971743,0.002162698,0.0001358336,0.0003151644,0.00008398086,0.0001279823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004572228,0.0001999373,0.9331448,0.002009016,0.0002885591,0.00003711947,0.002833496,0.0108914,0.02749686,0.0001534001,0.00000913868,0.01836406],"study_design_scores_gemma":[0.004517046,0.002479048,0.8246862,0.0007845202,0.002651847,0.00002829452,0.00003513697,0.02389756,0.1406748,0.00003139916,0.00001021474,0.0002039726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971737,0.00007446248,0.02530284,0.0007752258,0.0002521122,0.001349198,0.0001730929,0.0001341401,0.0002018779],"genre_scores_gemma":[0.9954404,0.002304219,0.001325202,0.000114754,0.00006197838,0.00004909421,0.0005238137,0.00003988214,0.0001406961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.113178,"threshold_uncertainty_score":0.6585386,"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."}}