{"id":"W4387575137","doi":"10.1111/itor.13384","title":"A heuristic algorithm to solve the one‐warehouse multiretailer problem with an emission constraint","year":2023,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Constraint (computer-aided design); Heuristic; Sensitivity (control systems); Mathematical optimization; Computer science; Limiting; Relaxation (psychology); Algorithm; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002069835,0.0001638768,0.0001225341,0.001342573,0.0006176797,0.0008029049,0.0006604037,0.00005665151,0.001611117],"category_scores_gemma":[0.0002121344,0.0001266374,0.00004404528,0.001913881,0.0001735215,0.001044895,0.00009763621,0.0004849452,0.0005726264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003003604,"about_ca_system_score_gemma":0.0001987319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001439216,"about_ca_topic_score_gemma":0.0009344218,"domain_scores_codex":[0.9970262,0.00005495484,0.0003260969,0.0004740089,0.001637772,0.0004809853],"domain_scores_gemma":[0.9981861,0.0003204759,0.00003808634,0.0002836016,0.001129681,0.00004211327],"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":[0.0008080687,0.001734197,0.003169188,0.000213878,0.000366465,0.0004103984,0.002397131,0.6998355,0.000639289,0.1044003,0.01161214,0.1744134],"study_design_scores_gemma":[0.001789385,0.0001343527,0.01010508,0.0002205221,0.0000228678,0.00001293245,0.0106872,0.7929084,0.0001177242,0.008862411,0.1746437,0.0004955232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.102422,0.00003156078,0.6850215,0.1574336,0.001301444,0.007943954,0.0001559922,0.0009239616,0.04476597],"genre_scores_gemma":[0.9790733,0.00001563181,0.009413237,0.001289585,0.000723389,0.001446698,0.0002244188,0.00005995297,0.007753723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8766513,"threshold_uncertainty_score":0.9993016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0743938146218444,"score_gpt":0.3536101937410626,"score_spread":0.2792163791192182,"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."}}