{"id":"W3041293865","doi":"10.22116/jiems.2020.110248","title":"Tactical and operational planning for socially responsible fresh agricultural supply chain","year":2020,"lang":"en","type":"article","venue":"Industrial Engineering and Management","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Supply chain; Pareto principle; Weighting; Scheduling (production processes); Operations research; Revenue; Multi-objective optimization; Constraint (computer-aided design); Computer science; Budget constraint; Environmental economics; Operations management; Business; Engineering; Economics; Microeconomics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001054981,0.0009551798,0.0005897243,0.0006832308,0.0007936206,0.001686712,0.0009125919,0.001191058,0.003209176],"category_scores_gemma":[0.001223008,0.000519314,0.0008195029,0.0009862413,0.0007088083,0.001399444,0.001324383,0.0009654182,0.0002496411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001306081,"about_ca_system_score_gemma":0.002901747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01428412,"about_ca_topic_score_gemma":0.01386793,"domain_scores_codex":[0.9993306,0.0002538459,0.0000267558,0.0001043254,0.0001699662,0.0001143594],"domain_scores_gemma":[0.9995744,0.0001738064,0.00008322131,0.00002741229,0.00009382181,0.00004750932],"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":[0.000009398694,0.00001230775,0.000273551,0.00002381007,0.000008673483,0.00005864221,0.00004174089,0.9864804,0.0004098554,0.007223731,0.0001656003,0.005292337],"study_design_scores_gemma":[0.000004182969,0.00001874879,0.000118787,0.000006839971,0.000005870126,0.00001558777,0.00005405316,0.9933853,0.0001606212,0.005564801,0.0006597117,0.000005454241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02680705,0.0001601757,0.9622536,0.0002817422,0.00002236004,0.0001147446,0.0001033997,0.0000702496,0.01018675],"genre_scores_gemma":[0.8099127,0.0005268978,0.1818404,0.00008675332,0.00002006771,0.0004590677,0.0002278003,0.0000452464,0.006880949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01428412,"threshold_uncertainty_score":0.02840197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404649608995563,"score_gpt":0.2312311867724489,"score_spread":0.1907662258728925,"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."}}