{"id":"W4390050745","doi":"10.3390/su16010098","title":"An Adaptive Sequential Decision-Making Approach for Perishable Food Procurement, Storage and Distribution Using Hyperconnected Logistics","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Procurement; Shelf life; Fresh food; Computer science; Business; Operations research; Distribution (mathematics); Food industry; Environmental economics; Marketing; Engineering; Economics; Mathematics; Food science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002507545,0.00201299,0.001736644,0.0009113221,0.0009082928,0.00229606,0.002387416,0.001958876,0.00419571],"category_scores_gemma":[0.001992252,0.00136265,0.001536557,0.001307158,0.001054817,0.001318012,0.001366107,0.001692358,0.0003653052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002179265,"about_ca_system_score_gemma":0.002880858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01549262,"about_ca_topic_score_gemma":0.01252037,"domain_scores_codex":[0.9982792,0.0007050295,0.00007470221,0.0003838008,0.0003224645,0.000234687],"domain_scores_gemma":[0.9982376,0.0009861731,0.0002667964,0.00004867787,0.0003015528,0.0001591465],"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":[0.00003437426,0.00003025891,0.0001396077,0.00002794598,0.00002062534,0.00005369453,0.00002660195,0.9946972,0.0002883108,0.001450098,0.00007682545,0.003154402],"study_design_scores_gemma":[0.00001024727,0.00003274884,0.00003141053,0.000002831424,0.000008492648,0.000003581147,0.00001162372,0.9987953,0.00009684513,0.0009084974,0.00009478541,0.000003665386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03579668,0.0002281719,0.9581223,0.0002546498,0.00005231329,0.0002275172,0.00008100926,0.000166221,0.005071132],"genre_scores_gemma":[0.8384854,0.0003589842,0.1558174,0.0001255179,0.00005147381,0.0005594213,0.0001480408,0.00004465937,0.004409026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01549262,"threshold_uncertainty_score":0.03080487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03831225142177901,"score_gpt":0.2924543481173629,"score_spread":0.2541420966955839,"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."}}