{"id":"W3162029197","doi":"10.5267/j.dsl.2021.5.001","title":"A fuzzy optimization approach to strategic organ transplantation network design problem: A real case study","year":2021,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Supply chain network; Operations research; Fuzzy logic; Mathematical optimization; Goal programming; Measure (data warehouse); Supply chain; Risk analysis (engineering); Supply chain management; Artificial intelligence; Engineering; Data mining; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002035452,0.0001674536,0.00015239,0.0003676512,0.0006583228,0.0008261398,0.0003626713,0.0000269129,0.00007546074],"category_scores_gemma":[0.00006378458,0.000155749,0.0000386614,0.00415762,0.00006192982,0.001267901,0.0001349283,0.00008162711,0.0001076851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006266843,"about_ca_system_score_gemma":0.00005741605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008077148,"about_ca_topic_score_gemma":0.000335231,"domain_scores_codex":[0.9976049,0.00004177889,0.0004055376,0.0007039899,0.0008286131,0.0004151525],"domain_scores_gemma":[0.9991772,0.00003163933,0.00006751165,0.0003962245,0.0002844852,0.00004297879],"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":[0.00003290332,0.000197606,0.0007644666,0.00002497791,0.000006388339,0.0002931842,0.0005447831,0.99296,0.0004427748,0.00158144,0.001275376,0.001876084],"study_design_scores_gemma":[0.002015307,0.00007766189,0.005270666,0.00007918014,0.000176431,0.0002248354,0.01938631,0.9696596,0.00005628821,0.001643748,0.0004195506,0.0009903704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.41908,0.000002845878,0.5754346,0.0009808172,0.0002838192,0.000704672,5.04138e-7,0.00007792264,0.003434823],"genre_scores_gemma":[0.8888249,0.000006779416,0.106777,0.004072102,0.0001832132,0.00007108931,0.00001763546,0.00001305502,0.0000342274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4697449,"threshold_uncertainty_score":0.7966486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07169450635771908,"score_gpt":0.2797675946514673,"score_spread":0.2080730882937483,"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."}}