{"id":"W2349840246","doi":"","title":"Comparative study on domestic and abroad cold chain logistics system for agricultural products","year":2013,"lang":"en","type":"article","venue":"Journal of Beijing University of Agriculture","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cold chain; Agriculture; Business; Marketization; China; Supply chain; Agricultural economics; Product (mathematics); Industrial organization; Agricultural science; Marketing; Engineering; Environmental science; Economics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003019003,0.0001760495,0.0004731592,0.00002276216,0.0002428304,0.00004312618,0.0002851026,0.0001010507,0.00001076122],"category_scores_gemma":[0.00008766055,0.00006394872,0.000115971,0.0002916844,0.0001032533,0.0002076333,0.00005248341,0.000219364,0.000002920288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001004531,"about_ca_system_score_gemma":0.00001395085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001067731,"about_ca_topic_score_gemma":0.000123945,"domain_scores_codex":[0.9988702,0.0001398065,0.000281428,0.0002242661,0.0002922241,0.0001920592],"domain_scores_gemma":[0.9980409,0.0003807132,0.0005009921,0.00005170156,0.0008983899,0.0001273632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006931706,0.00328499,0.02533249,0.0004334698,0.0006765304,0.00007609483,0.01061254,0.001306827,0.9285477,0.001298572,0.02626102,0.001476597],"study_design_scores_gemma":[0.001215627,0.005302518,0.8508489,0.0002064425,0.0001901143,0.00007759251,0.1374323,0.00003674217,0.002991774,0.00002949034,0.001370276,0.0002982281],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974658,0.00009088816,0.00001844867,0.001180729,0.0001338155,0.0009181377,0.0000395108,0.00002005499,0.0001325819],"genre_scores_gemma":[0.9992094,0.000006216942,0.0003692956,0.000009471907,0.0001682657,8.718806e-7,0.000007548746,6.537875e-7,0.0002282998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9255559,"threshold_uncertainty_score":0.2607753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02038391791465741,"score_gpt":0.2217220627765743,"score_spread":0.2013381448619169,"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."}}