{"id":"W2747941871","doi":"10.1016/j.tifs.2017.08.014","title":"Food safety for food security: Relationship between global megatrends and developments in food safety","year":2017,"lang":"en","type":"article","venue":"Trends in Food Science & Technology","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":567,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Fonterra Co-Operative Group","keywords":"Food security; Business; Food safety; Enabling; Context (archaeology); Supply chain; Population; Food systems; Food processing; Food packaging; Marketing; Engineering; Agriculture; Geography; Political science; Environmental health","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001287339,0.0002874439,0.0004423822,0.0003988996,0.001382357,0.0001616248,0.001298126,0.0004310797,0.0000120484],"category_scores_gemma":[0.001009661,0.0001621887,0.00008570438,0.003143387,0.001620254,0.0005622238,0.0006215873,0.0003829546,0.000001321408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004781029,"about_ca_system_score_gemma":0.0001095478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004197137,"about_ca_topic_score_gemma":0.01159113,"domain_scores_codex":[0.9970676,0.00007026245,0.0006084863,0.0009918057,0.0003593958,0.0009024947],"domain_scores_gemma":[0.9989268,0.0001650865,0.0002544327,0.0003535149,0.0001306559,0.0001695179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009174387,0.0001106966,0.5434461,0.00001233556,0.00001397766,9.600217e-7,0.0001805341,0.000002847161,0.0000966384,0.0506656,0.00001214973,0.4053665],"study_design_scores_gemma":[0.00088196,0.003786291,0.9079625,0.00002600142,0.000007496678,0.00001456178,0.002570113,0.00002094516,0.0005416283,0.07898302,0.004865117,0.0003403455],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877307,0.0001841715,0.00001191557,0.008303014,0.0001978669,0.000346496,0.000307166,0.0001367931,0.002781915],"genre_scores_gemma":[0.9993728,0.00001273886,0.0003893304,0.0000279091,0.00005155412,0.00006830803,0.0000284257,0.000002170677,0.00004674666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4050261,"threshold_uncertainty_score":0.9999177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05016533365720671,"score_gpt":0.3080420530402038,"score_spread":0.2578767193829971,"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."}}