{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004047513,0.0004077132,0.001431689,0.002955988,0.000258589,0.00006247547,0.0006289987,0.0004196878,0.00006579234],"category_scores_gemma":[0.003948072,0.0003644034,0.00006239751,0.001036771,0.0006389438,0.0003791332,0.003587032,0.0007847641,0.00007773271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004167825,"about_ca_system_score_gemma":0.0003011673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004217525,"about_ca_topic_score_gemma":0.000374193,"domain_scores_codex":[0.9953223,0.0001149996,0.002765954,0.0005549528,0.0006907845,0.0005509965],"domain_scores_gemma":[0.9968138,0.0005845654,0.001198795,0.0008857079,0.0004146043,0.0001024849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008674359,0.001834509,0.005393724,0.01441478,0.005283662,0.00122025,0.1211609,0.003395112,0.00003213386,0.6617336,0.07211537,0.1125485],"study_design_scores_gemma":[0.00728931,0.004368752,0.0003649997,0.01552846,0.0008790614,0.0004732861,0.1335737,0.01552744,0.0002817617,0.1510371,0.6667643,0.003911863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3694337,0.05248312,0.001662159,0.05099393,0.007924314,0.01824903,0.001271378,0.001208625,0.4967737],"genre_scores_gemma":[0.03249168,0.1946882,0.2163619,0.01993912,0.0006419854,0.0005155437,0.0005135994,0.0003276272,0.5345204],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.594649,"threshold_uncertainty_score":0.9998808,"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."}}