{"id":"W3049198493","doi":"10.1016/j.orhc.2021.100290","title":"A decision integration strategy for short-term demand forecasting and ordering for red blood cell components","year":2021,"lang":"en","type":"article","venue":"Operations Research for Health Care","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Blood Services; McMaster University; University of Calgary","funders":"Mitacs; Canadian Blood Services","keywords":"Economic shortage; Supply chain; Demand forecasting; Key (lock); Inventory management; Supply and demand; Blood management; Supply chain management","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":[0.00438722,0.001282307,0.001249377,0.002660809,0.001227042,0.004140626,0.001514217,0.001369682,0.007596646],"category_scores_gemma":[0.005301362,0.0006691706,0.001213187,0.002973982,0.000585442,0.004573352,0.002303452,0.00119317,0.0009591934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002028874,"about_ca_system_score_gemma":0.004510677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02138954,"about_ca_topic_score_gemma":0.01712335,"domain_scores_codex":[0.9978998,0.0006987811,0.0001731131,0.0003629082,0.0006394403,0.0002260638],"domain_scores_gemma":[0.9974753,0.001010863,0.0001608805,0.0001751078,0.0009661026,0.0002116316],"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":[0.0006420024,0.001273895,0.006941397,0.0001423847,0.0004251843,0.0004515096,0.0003393766,0.511658,0.006014211,0.03864903,0.007702787,0.4257603],"study_design_scores_gemma":[0.00002692484,0.0001289633,0.0007790307,0.00001449901,0.00007318658,0.00002957741,0.0001532922,0.9831714,0.001042667,0.01222786,0.002332135,0.00002057932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06671,0.0003962883,0.9070733,0.001669182,0.0001234177,0.0005332049,0.0004819582,0.001453439,0.02155924],"genre_scores_gemma":[0.6420712,0.0002641396,0.3501798,0.0003329644,0.00007991077,0.0002623737,0.001178183,0.00008822384,0.005543102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02138954,"threshold_uncertainty_score":0.04253006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1697736990848324,"score_gpt":0.4172118591312488,"score_spread":0.2474381600464164,"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."}}