{"id":"W4403420321","doi":"10.1111/tme.13104","title":"Pitfalls of reasoning in hospital‐based transfusion medicine","year":2024,"lang":"en","type":"review","venue":"Transfusion Medicine","topic":"Clinical Reasoning and Diagnostic Skills","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Canadian Blood Services; University of Toronto","funders":"Canadian Blood Services","keywords":"Transfusion medicine; Cognitive bias; Cognition; Satisficing; Psychology; Framing effect; Psychological intervention; Health care; Confirmation bias; Fallacy; Causal inference; Medicine; Social psychology; Blood transfusion; Computer science; Psychiatry; Persuasion; Artificial intelligence; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0121549,0.001074323,0.002307081,0.004552685,0.0005139839,0.003118508,0.001546565,0.001939677,0.002322253],"category_scores_gemma":[0.04506953,0.0006276523,0.002860314,0.004362208,0.00185437,0.002381554,0.001627441,0.002094498,0.0003061196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003144752,"about_ca_system_score_gemma":0.008183694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006067052,"about_ca_topic_score_gemma":0.01003544,"domain_scores_codex":[0.9868698,0.007492001,0.002182891,0.0005407805,0.002665435,0.0002491795],"domain_scores_gemma":[0.9363191,0.0539857,0.005886795,0.0005883649,0.002945439,0.0002745823],"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":[0.0001819292,0.00005098242,0.001179695,0.2161682,0.002399902,0.0001474443,0.0009202704,0.0007254226,0.000136009,0.005378948,0.006538187,0.7661731],"study_design_scores_gemma":[0.0002280765,0.0003249393,0.007590637,0.6809196,0.01075393,0.002234109,0.002009839,0.0008434234,0.0008942885,0.01733518,0.2767111,0.0001548908],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003661402,0.9984373,0.0001853414,0.00051566,0.00007363214,0.00001740856,0.0000117977,0.000003104346,0.0003895976],"genre_scores_gemma":[0.008906693,0.9893968,0.0007925638,0.0006181388,0.0001187653,0.00003814806,0.00003133201,0.000002706257,0.00009487109],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0121549,"threshold_uncertainty_score":0.064282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0501356519299426,"score_gpt":0.400574664290361,"score_spread":0.3504390123604184,"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."}}