{"id":"W3156704517","doi":"10.1051/e3sconf/202125103001","title":"Food Waste in Developed Countries and Cold Chain Logistics","year":2021,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Cold chain; Business; Supply chain; Production (economics); Food waste; Agriculture; Food packaging; Food processing; Supply chain management; Fresh food; Commerce; Agricultural economics; Marketing; Waste management; Engineering; Economics; Food science; Shelf life; Geography","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":[0.0001914316,0.00007702579,0.0001766827,0.0000112977,0.00005108436,0.00003870074,0.00008159233,0.0000615141,0.0001405794],"category_scores_gemma":[0.0001594911,0.00003282483,0.00002247577,0.0002204192,0.0001813119,0.00004971307,0.00005065439,0.00006230578,6.571398e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000108976,"about_ca_system_score_gemma":0.0002675665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009381308,"about_ca_topic_score_gemma":0.003284951,"domain_scores_codex":[0.9992898,0.00007678424,0.0001973114,0.0001719135,0.0001241775,0.0001400308],"domain_scores_gemma":[0.9995272,0.0001521759,0.00005482867,0.0000334299,0.0001882781,0.00004415795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001815097,0.0003965968,0.4071516,0.0002573147,0.00006363594,0.00003305432,0.0008525093,0.00003310684,0.0640516,0.3783375,0.0005686072,0.148073],"study_design_scores_gemma":[0.001117732,0.001990899,0.4667663,0.0001953321,0.00002789301,0.00002674973,0.2228588,0.0006272659,0.1038812,0.01519629,0.1864842,0.000827303],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937875,0.0004983379,0.000003802655,0.002276344,0.00008088368,0.0000802248,0.00002204737,0.0000121811,0.003238654],"genre_scores_gemma":[0.9993616,0.0002415829,0.00004351483,0.00007439088,0.00003569347,0.000004691221,0.000007779236,2.741269e-7,0.000230459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3631412,"threshold_uncertainty_score":0.1833079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03301687276573426,"score_gpt":0.2349219463322015,"score_spread":0.2019050735664673,"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."}}