{"id":"W3136389483","doi":"10.3233/jifs-202529","title":"Multi-objective reference point based enriched swarm optimization with an application to blood supply chain under natural disaster","year":2021,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Particle swarm optimization; Mathematical optimization; Computer science; Multi-objective optimization; Pareto principle; Extreme point; Swarm behaviour; Supply chain; Algorithm; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.000671525,0.0002058493,0.0002999027,0.0003723919,0.0001318873,0.0005258216,0.0002295514,0.00007827202,0.00008734317],"category_scores_gemma":[0.0001150415,0.0001554289,0.00008117197,0.0006755243,0.00002110712,0.001554553,0.00003457716,0.0002834931,0.00004418966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006184623,"about_ca_system_score_gemma":0.0001007288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002207468,"about_ca_topic_score_gemma":0.0002867503,"domain_scores_codex":[0.9982198,0.00008973656,0.0006450975,0.0002893307,0.0005611915,0.0001948025],"domain_scores_gemma":[0.9971166,0.00009689525,0.0007511935,0.0002349057,0.001743031,0.00005735091],"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":[0.002008204,0.00405805,0.01014259,0.0006241358,0.0007967316,0.0001689933,0.001548526,0.9369357,0.0197834,0.01771641,0.0003921905,0.005825091],"study_design_scores_gemma":[0.01273285,0.001284468,0.0237181,0.001935636,0.002277856,0.0007753475,0.06285848,0.8492994,0.01798011,0.0006026257,0.02394016,0.002595013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2082126,0.0005494489,0.7837901,0.00334197,0.001104907,0.0008327726,0.000005776404,0.00007526584,0.002087202],"genre_scores_gemma":[0.9912662,0.00002478053,0.00638208,0.001544151,0.0004985028,0.00002531287,0.00004899698,0.00003046283,0.0001794954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7830536,"threshold_uncertainty_score":0.6338208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0211818103486093,"score_gpt":0.257958212457696,"score_spread":0.2367764021090867,"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."}}