{"id":"W3012860294","doi":"10.1080/10255842.2020.1742709","title":"Blood transfusion prediction using restricted Boltzmann machines","year":2020,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Restricted Boltzmann machine; Task (project management); Identification (biology); Computer science; Blood transfusion; Artificial intelligence; Machine learning; Data mining; Medicine; Medical emergency; Pattern recognition (psychology); Deep learning; Engineering; Surgery","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":[0.0009074659,0.000496065,0.00081654,0.0005641285,0.0001801029,0.0006311291,0.0006421173,0.0005547268,0.0009793236],"category_scores_gemma":[0.003222376,0.0003735854,0.0005486416,0.0003681859,0.0003031115,0.0005803063,0.000560536,0.0008542674,0.000348759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003966449,"about_ca_system_score_gemma":0.0005668881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003225709,"about_ca_topic_score_gemma":0.002208293,"domain_scores_codex":[0.9995614,0.0001715242,0.00003181084,0.00009555068,0.0000772538,0.00006247475],"domain_scores_gemma":[0.9989333,0.0007327637,0.0001121983,0.0000570218,0.0001279886,0.00003676082],"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":[0.0001728444,0.00008532063,0.004776969,0.00004029601,0.00007411435,0.0000893192,0.0000334356,0.9083869,0.002185794,0.001634511,0.00113081,0.08138966],"study_design_scores_gemma":[0.000002124537,0.000008753831,0.0002804954,0.000001787181,0.000003616076,0.000009107345,0.000002406732,0.9983171,0.0003003043,0.001013807,0.00005789376,0.000002623693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1501138,0.001070579,0.8452235,0.0005736593,0.0001313026,0.00004609638,0.00018654,0.001028757,0.001625804],"genre_scores_gemma":[0.9599133,0.0002400489,0.03807141,0.0001120696,0.00005301072,0.00005045022,0.0002074015,0.00003414648,0.001318194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003225709,"threshold_uncertainty_score":0.006413877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02876329382135677,"score_gpt":0.2847331832428003,"score_spread":0.2559698894214436,"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."}}