{"id":"W3165615601","doi":"10.3233/shti210153","title":"Using Interactive Visual Analytics to Optimize in Real-Time Blood Products Inventory at a Blood Bank","year":2021,"lang":"en","type":"book-chapter","venue":"Studies in health technology and informatics","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Canadian Blood Services","keywords":"Dashboard; Analytics; Computer science; Product (mathematics); Visualization; Inventory management; Visual analytics; Blood product; Blood transfusion; Operations management; Database; Medicine; Engineering; Data mining; 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":[0.0005701714,0.0009094372,0.0003097021,0.000847129,0.0002243545,0.002416817,0.0009124603,0.0005497641,0.0111297],"category_scores_gemma":[0.001543754,0.00027315,0.0003495917,0.0009039338,0.0003466747,0.001588633,0.0009301145,0.0008060453,0.002806434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004245737,"about_ca_system_score_gemma":0.0003655104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357978,"about_ca_topic_score_gemma":0.001738678,"domain_scores_codex":[0.9997656,0.00005260326,0.00001051531,0.00004211131,0.0001098364,0.0000193104],"domain_scores_gemma":[0.9991446,0.0005771506,0.00002946488,0.00005230698,0.0001562955,0.00004026419],"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":[0.0002233123,0.0001617125,0.001290415,0.0008071127,0.00004582684,0.00042434,0.001334485,0.05093483,0.04217389,0.03942439,0.1120396,0.7511401],"study_design_scores_gemma":[0.00008609693,0.000235657,0.003025876,0.000524586,0.00007968659,0.0006562906,0.0007361961,0.4471932,0.0404929,0.06313816,0.4436783,0.0001530879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01711338,0.003033469,0.8760734,0.001124808,0.0003981663,0.0001595642,0.0009965575,0.01819013,0.08291055],"genre_scores_gemma":[0.1341793,0.005654497,0.7675602,0.0006236735,0.000239977,0.0003117336,0.002316753,0.003074549,0.08603924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0111297,"threshold_uncertainty_score":0.03723258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.242356127798014,"score_gpt":0.4647581005679444,"score_spread":0.2224019727699303,"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."}}