{"id":"W4386742044","doi":"10.5267/j.dsl.2023.6.002","title":"Exploring managerial insights through multi criteria decision making techniques in pharmacy inventory classification problem","year":2023,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiple-criteria decision analysis; Context (archaeology); Pharmacy; Inventory management; Supply chain management; Knowledge management; Supply chain; Management science; Business; Marketing; Process management; Computer science; Operations management; Medicine; Operations research; Economics; Nursing; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01337568,0.001401837,0.001459574,0.004231523,0.001330354,0.004440375,0.001442116,0.001863419,0.003247579],"category_scores_gemma":[0.0246248,0.0007516411,0.001663017,0.003323582,0.001631062,0.00244565,0.002257156,0.002736953,0.0001644164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002473078,"about_ca_system_score_gemma":0.003343531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004096424,"about_ca_topic_score_gemma":0.005858453,"domain_scores_codex":[0.9912307,0.006758909,0.0003357949,0.000426161,0.0009073144,0.0003411977],"domain_scores_gemma":[0.9696343,0.0276183,0.0009866771,0.0004221294,0.0009974446,0.0003411479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002259105,0.0004850353,0.005062169,0.001138214,0.0003410943,0.0005028582,0.001429398,0.7860661,0.001368625,0.09523805,0.00132344,0.1068191],"study_design_scores_gemma":[0.00002907012,0.0001094991,0.0005869474,0.0001596679,0.00004632253,0.00005669243,0.0005672287,0.9193933,0.0003598348,0.07747196,0.001189683,0.00002966749],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08411314,0.001192618,0.9034017,0.002246595,0.00007903028,0.0005579263,0.000212965,0.00007983964,0.008116105],"genre_scores_gemma":[0.5169511,0.000686423,0.4807622,0.0001777093,0.00006900273,0.0004607437,0.0001183182,0.00001729839,0.0007571897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01337568,"threshold_uncertainty_score":0.07073826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5182005756656943,"score_gpt":0.5007403021530226,"score_spread":0.01746027351267176,"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."}}