{"id":"W2975026108","doi":"10.1108/jm2-12-2018-0220","title":"An integrated DEA-based approach for evaluating and sizing health care supply chains","year":2019,"lang":"en","type":"article","venue":"Journal of Modelling in Management","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Supply chain; Data envelopment analysis; Computer science; Sizing; Interval (graph theory); Supply chain management; Operations research; Originality; Mathematical optimization; Business; Engineering; Mathematics; Marketing","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004887485,0.001195489,0.001261176,0.003224029,0.0006141604,0.002923504,0.001025864,0.0007238714,0.002624892],"category_scores_gemma":[0.01004427,0.0005842308,0.001111103,0.003171154,0.0007319869,0.001529381,0.001769068,0.000946626,0.0002148345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002128629,"about_ca_system_score_gemma":0.00282197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005371363,"about_ca_topic_score_gemma":0.006042625,"domain_scores_codex":[0.9951957,0.002587106,0.0003394864,0.0005564041,0.001170486,0.0001508129],"domain_scores_gemma":[0.9957196,0.002283784,0.0006127354,0.0002701921,0.001035752,0.00007794367],"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":[0.00006769523,0.0001199481,0.00252845,0.0002949541,0.0001708014,0.00009240662,0.0001949858,0.8617979,0.002893411,0.02970119,0.0004111997,0.101727],"study_design_scores_gemma":[0.00001441244,0.000115552,0.0007986825,0.00006163855,0.00004264633,0.00003096929,0.0001323854,0.9790075,0.001253475,0.01673387,0.001789745,0.00001917069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008559136,0.0001537464,0.9884595,0.00007353057,0.00001226315,0.0002284174,0.0001100308,0.00007437824,0.002328987],"genre_scores_gemma":[0.2566189,0.0002783291,0.7414042,0.00004383158,0.00001858468,0.0006000361,0.0002411126,0.00002265199,0.0007723674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005371363,"threshold_uncertainty_score":0.02584785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1356984365732233,"score_gpt":0.4256992095128992,"score_spread":0.290000772939676,"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."}}