{"id":"W4413476772","doi":"10.1016/j.tmrv.2025.150926","title":"Artificial Intelligence and Machine Learning in Transfusion Practice: An Analytical Assessment","year":2025,"lang":"en","type":"article","venue":"Transfusion Medicine Reviews","topic":"Blood transfusion and management","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; Alberta Health; University of Calgary; Canadian Blood Services; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Artificial intelligence; Medicine; Intensive care medicine; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003263808,0.0003531418,0.001093928,0.0006176832,0.0001696415,0.00002172957,0.0001387607,0.000158061,0.0009033734],"category_scores_gemma":[0.000373096,0.0002537561,0.0001305895,0.001157677,0.0001946996,0.0001959994,0.00003115077,0.0009982901,0.00001465549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008155408,"about_ca_system_score_gemma":0.0001098179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00120409,"about_ca_topic_score_gemma":0.00142587,"domain_scores_codex":[0.9965277,0.0005829506,0.001311105,0.0007133317,0.0005028466,0.0003620781],"domain_scores_gemma":[0.9988483,0.0002379784,0.00009629649,0.000422307,0.00009687908,0.0002982839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005395108,0.00101446,0.006456504,0.001026478,0.00005111034,0.000113423,0.00103509,0.00001876562,0.003819039,0.01707934,0.000217116,0.9686292],"study_design_scores_gemma":[0.007081746,0.006510675,0.04167481,0.01124012,0.004203974,0.0003130844,0.006890731,0.05775246,0.001223551,0.002626484,0.8593417,0.001140692],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1700941,0.06759132,0.4369827,0.2218059,0.001261795,0.012635,0.000006321293,0.0005721303,0.08905076],"genre_scores_gemma":[0.1696031,0.8162193,0.005617178,0.006990257,0.0001837827,0.0001533803,0.00007388591,0.00004107918,0.001118026],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9674885,"threshold_uncertainty_score":0.9999915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09254837046801645,"score_gpt":0.4197814860200182,"score_spread":0.3272331155520018,"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."}}