{"id":"W2153218134","doi":"10.1111/cjag.12039","title":"Identifying Strategies to Mitigate Handling Risks in the Canadian Grain Supply Chain","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Supply chain; Declaration; Business; Incentive; Misrepresentation; Quality (philosophy); Identification (biology); Environmental economics; Product (mathematics); Risk analysis (engineering); Industrial organization; Marketing; Computer science; Economics; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002217457,0.0004078114,0.0006350981,0.0002484112,0.0007163681,0.0009702902,0.001454646,0.0002305494,0.0002816289],"category_scores_gemma":[0.0002992921,0.0001924835,0.0003099801,0.0004469395,0.000157175,0.0007183466,0.00002787486,0.0006299474,0.00005518665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002254627,"about_ca_system_score_gemma":0.0007500742,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9048626,"about_ca_topic_score_gemma":0.9999132,"domain_scores_codex":[0.9966423,0.0002675021,0.001071623,0.0005177234,0.0000414975,0.001459384],"domain_scores_gemma":[0.9963125,0.0003804609,0.0004163906,0.0001939362,0.0002024919,0.002494239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003120676,0.0002233719,0.5179296,0.0002671203,0.0008249028,0.001065565,0.06853952,0.08472286,0.008073929,0.1636605,0.02246371,0.1319169],"study_design_scores_gemma":[0.000343175,0.000491636,0.9501635,0.00009460889,0.00002907331,0.000367215,0.01421839,0.0001334046,0.00008022507,0.006201068,0.02726766,0.0006100888],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707877,0.0001391141,0.00000167532,0.02616976,0.0009837105,0.0004998791,0.0002362259,0.000009268556,0.001172646],"genre_scores_gemma":[0.9973028,0.0000127065,0.0000997961,0.001409907,0.0009852336,0.00002701583,0.00007582874,0.00000548282,0.00008127817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4322339,"threshold_uncertainty_score":0.9356531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0449228004690122,"score_gpt":0.2022285376724052,"score_spread":0.157305737203393,"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."}}