{"id":"W4388596752","doi":"10.1111/trf.17582","title":"Machine learning in transfusion medicine: A scoping review","year":2023,"lang":"en","type":"review","venue":"Transfusion","topic":"Autopsy Techniques and Outcomes","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University College London; National Institute for Health and Care Research; UCLH Biomedical Research Centre; UK Research and Innovation","keywords":"Transfusion medicine; Medicine; Intensive care medicine; MEDLINE; Blood transfusion; Computer science; Surgery; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006265058,0.001197187,0.003274936,0.00921879,0.0007153473,0.003127852,0.002102731,0.003062396,0.00928128],"category_scores_gemma":[0.03381735,0.0006385381,0.003487132,0.01021076,0.001030835,0.003179495,0.001694925,0.002804903,0.001188442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002938775,"about_ca_system_score_gemma":0.007875034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005558087,"about_ca_topic_score_gemma":0.008860118,"domain_scores_codex":[0.9973036,0.000911089,0.0007254876,0.0002477484,0.0006896931,0.0001224233],"domain_scores_gemma":[0.9628493,0.03207798,0.002004115,0.0003310651,0.002499337,0.0002381816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001061461,0.00006520707,0.0005718957,0.2806628,0.001087391,0.000130868,0.0002353289,0.00100911,0.0001221217,0.004551784,0.03098623,0.6804711],"study_design_scores_gemma":[0.00003157587,0.0000827655,0.001399707,0.7523435,0.00225061,0.000430587,0.0001886567,0.0005122814,0.00012714,0.004180738,0.2384103,0.00004217069],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005803875,0.9986436,0.0001334618,0.0006597448,0.0001453548,0.00001901304,0.00003413107,0.000005065245,0.0003016197],"genre_scores_gemma":[0.0008665707,0.9982044,0.000267785,0.0003525112,0.0001473051,0.00003497826,0.00004053539,0.000003231388,0.00008262502],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00928128,"threshold_uncertainty_score":0.03313321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08573351490376561,"score_gpt":0.4122714223581637,"score_spread":0.326537907454398,"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."}}