{"id":"W4378226772","doi":"10.3390/foods12112124","title":"Finding Traceability Granularity Influencing Factors Using Rough Set Method: An Empirical Analysis of Vegetable Companies in Tianjin City, China","year":2023,"lang":"en","type":"article","venue":"Foods","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"Chinese Academy of Agricultural Sciences; National Natural Science Foundation of China","keywords":"Traceability; Granularity; Revenue; Business; Quality (philosophy); Certification; Computer science; Operations management; Process management; Marketing; Environmental economics; Operations research; Industrial organization; Mathematics; Finance; Economics","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":[0.002408565,0.0002400089,0.0007409917,0.000149899,0.0002125901,0.00006223156,0.0004065752,0.0002133304,0.000210787],"category_scores_gemma":[0.0003591407,0.0001163965,0.000304643,0.004977053,0.000120239,0.0003601361,0.0001791396,0.0003169177,0.000001917552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327518,"about_ca_system_score_gemma":0.0000236399,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008608351,"about_ca_topic_score_gemma":0.01642452,"domain_scores_codex":[0.9970248,0.0008326764,0.0006143089,0.0006212594,0.0004067853,0.000500208],"domain_scores_gemma":[0.9986804,0.0007423291,0.0001630491,0.0002150844,0.00006069197,0.0001384821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002521259,0.000157764,0.9695265,0.00002602335,0.00008370333,0.000002195148,0.002582639,0.01257829,0.01450907,0.000007112739,0.000004014284,0.0004974827],"study_design_scores_gemma":[0.0001011284,0.0001678446,0.913158,0.00001086343,0.0001125449,6.074876e-7,0.001291012,0.08202077,0.001999524,0.0008995652,0.00003221892,0.000205956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988701,0.00002720726,0.00004896444,0.0001932525,0.00007938524,0.0002537697,0.0003301009,0.0001688383,0.00002832184],"genre_scores_gemma":[0.9981196,0.000001222171,0.001529289,0.00001895566,0.00003464825,0.000005659996,0.0002819724,0.00000203822,0.000006614168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06944247,"threshold_uncertainty_score":0.9979934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1524435196278379,"score_gpt":0.3846886075872638,"score_spread":0.2322450879594259,"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."}}