{"id":"W4281631609","doi":"10.3233/shti220142","title":"Using Interactive Visual Analytics to Optimize Blood Products Inventory at a Blood Bank","year":2022,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Canadian Blood Services","keywords":"Dashboard; Audit; Analytics; Computer science; Blood product; Product (mathematics); Visualization; Inventory management; Blood transfusion; Process management; Operations management; Database; Business; Medicine; Data mining; Engineering; Accounting; Surgery","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":[0.001910062,0.001038029,0.0003673681,0.001940814,0.0005018478,0.002703194,0.000864493,0.0006490824,0.005002982],"category_scores_gemma":[0.006779027,0.0003146875,0.0004664711,0.001117785,0.0005287391,0.002072028,0.001690275,0.0009225013,0.0006625405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005187028,"about_ca_system_score_gemma":0.0009109613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002372475,"about_ca_topic_score_gemma":0.003701542,"domain_scores_codex":[0.9993041,0.0002336254,0.00005787676,0.0001297336,0.0002092318,0.00006552363],"domain_scores_gemma":[0.9947595,0.003559273,0.0003727881,0.0004566529,0.0005765822,0.0002751797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003121955,0.001192398,0.04258174,0.001801094,0.0002556665,0.002914894,0.01575701,0.1242408,0.09998544,0.02407727,0.04414594,0.6399258],"study_design_scores_gemma":[0.0003288408,0.0008830747,0.02815044,0.000618723,0.0002334812,0.0006201189,0.00575558,0.7699792,0.06495076,0.04254855,0.08560229,0.0003288907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3776158,0.0005584162,0.5459316,0.003090695,0.0002657615,0.0006213877,0.005256899,0.04565775,0.02100165],"genre_scores_gemma":[0.6099135,0.0004605446,0.3817126,0.000276199,0.00005781602,0.0002449939,0.002252562,0.001230707,0.003851034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005002982,"threshold_uncertainty_score":0.01673663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07814047328667809,"score_gpt":0.3722782023122505,"score_spread":0.2941377290255724,"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."}}