{"id":"W4393073723","doi":"10.5267/j.dsl.2023.12.008","title":"A hybrid matheuristic approach for the integrated location routing problem of the pineapple supply chain","year":2024,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Vehicle routing problem; Routing (electronic design automation); Computer science; Business; Mathematical optimization; Mathematics; Marketing; Computer network","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":[0.001738714,0.00008518437,0.00008903262,0.00002378434,0.000453313,0.00020353,0.0006396304,0.00001935433,0.00001260608],"category_scores_gemma":[0.0003544776,0.00002141024,0.00009245639,0.001526757,0.0004830179,0.0001420439,0.00009461215,0.0001075475,0.000001706377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006470062,"about_ca_system_score_gemma":0.0000459262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008263622,"about_ca_topic_score_gemma":0.000005790154,"domain_scores_codex":[0.998758,0.0000466002,0.0002306806,0.0003310139,0.0004159675,0.000217705],"domain_scores_gemma":[0.9991596,0.0004704744,0.0000613154,0.0001196609,0.0001555414,0.0000334508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003589412,0.00006239172,0.0004132222,0.00003344189,0.000006896796,5.114848e-7,0.0005216164,0.002048534,0.3053439,0.003187072,0.0054851,0.6828614],"study_design_scores_gemma":[0.0003681895,0.0003548587,0.06706385,0.0002721677,0.00005765744,0.0001044354,0.03050656,0.8028834,0.03415379,0.0085561,0.05507509,0.0006038756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9561401,0.00007355586,0.02815192,0.01457526,0.0002463483,0.0007132997,0.00001859025,0.0000384657,0.00004245311],"genre_scores_gemma":[0.9980836,0.000002286169,0.001335105,0.0003948842,0.0000701852,0.00004732776,0.000005951574,8.024365e-7,0.00005984721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8008349,"threshold_uncertainty_score":0.3486563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01780958400283422,"score_gpt":0.2473540334069166,"score_spread":0.2295444494040824,"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."}}