{"id":"W4247802898","doi":"10.32920/ryerson.14648022.v1","title":"Nitrogen-bearing toxins &amp; the environment : food-safety monitoring systems for the quality assurance of vegetable protein products","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Melamine detection and toxicity","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McGill University","funders":"Canadian Food Inspection Agency","keywords":"Melamine; Cyanuric acid; Quality assurance; Food safety; Chemistry; Food science; Contamination; Nitrogen; Biotechnology; Chromatography; Engineering; Biology; Organic chemistry; Operations management","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011495,0.0003857893,0.0002605909,0.000449081,0.000344543,0.0007231461,0.0004018971,0.000602875,0.0009471163],"category_scores_gemma":[0.0005871673,0.0001834162,0.0001481007,0.0003293247,0.0003991012,0.0005901508,0.0005233301,0.0002498159,0.0004826118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008775937,"about_ca_system_score_gemma":0.00102964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002933055,"about_ca_topic_score_gemma":0.004852034,"domain_scores_codex":[0.9991854,0.0001474256,0.0000231687,0.0001659972,0.000431333,0.0000467046],"domain_scores_gemma":[0.9996493,0.00005499169,0.00009559846,0.00003872803,0.0001375334,0.00002388428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004341675,0.00006380588,0.01681993,0.0002941687,0.00003645994,0.0001536412,0.0001455713,0.001921738,0.8799438,0.0007264625,0.0007014522,0.09875882],"study_design_scores_gemma":[0.00002015899,0.0004968542,0.04134537,0.0000620363,0.00005543017,0.0005869506,0.0002050401,0.03744158,0.9025111,0.001026768,0.0162095,0.0000393346],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7825648,0.006225414,0.1968399,0.0008100633,0.00007215334,0.0002656071,0.000900598,0.003542898,0.008778621],"genre_scores_gemma":[0.8952298,0.001105595,0.099535,0.0001561518,0.00002091164,0.00005721421,0.000474102,0.00008062112,0.003340541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002933055,"threshold_uncertainty_score":0.006367385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07132963644433554,"score_gpt":0.2597047791976997,"score_spread":0.1883751427533641,"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."}}