{"id":"W3201484950","doi":"10.1007/s12351-021-00674-x","title":"Designing pharmaceutical supply chain networks with perishable items considering congestion","year":2021,"lang":"en","type":"article","venue":"Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kwantlen Polytechnic University; University of British Columbia","funders":"","keywords":"Supply chain; Computer science; Metric (unit); Sensitivity (control systems); Computational intelligence; Job shop scheduling; Production (economics); Scheduling (production processes); Operations research; Mathematical optimization; Greenhouse gas; Supply chain management; Supply chain network; Risk analysis (engineering); Operations management; Business; Economics; Microeconomics; Schedule; Engineering; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002273049,0.0001682131,0.0001673962,0.0003125666,0.0008255807,0.001616896,0.0002058407,0.00007122054,0.002865758],"category_scores_gemma":[0.0007253691,0.0001596418,0.00003565037,0.001120576,0.0001612578,0.001089387,0.0003860843,0.0004927374,0.0002025825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000181741,"about_ca_system_score_gemma":0.0002682905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000232873,"about_ca_topic_score_gemma":0.000101377,"domain_scores_codex":[0.9973392,0.0001208248,0.0002331876,0.000494074,0.001059453,0.0007532174],"domain_scores_gemma":[0.9977428,0.0003703138,0.00003834464,0.0002442865,0.001561838,0.00004243412],"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":[0.0005375598,0.0004809969,0.06925642,0.000788417,0.0002834289,0.002626978,0.0002308716,0.4775096,0.008720931,0.3384288,0.08795294,0.0131831],"study_design_scores_gemma":[0.001890371,0.00004523697,0.005934482,0.0002237588,0.00003933457,0.00004095133,0.006748017,0.6239418,0.001627105,0.001037152,0.3579173,0.0005544786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3799799,0.005189169,0.1855802,0.1155598,0.00170962,0.006596428,0.0000148847,0.0009740534,0.3043959],"genre_scores_gemma":[0.9861348,0.0000375042,0.00289045,0.002289938,0.001398219,0.0002211305,0.0001731559,0.00004749429,0.00680735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6061549,"threshold_uncertainty_score":0.9994195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07239243685779077,"score_gpt":0.3358231940803073,"score_spread":0.2634307572225165,"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."}}