{"id":"W3204666190","doi":"10.1016/j.crfs.2021.09.010","title":"Application of non-target analysis to study the thermal transformation of malachite and leucomalachite green in brook trout and shrimp","year":2021,"lang":"en","type":"article","venue":"Current Research in Food Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Shrimp; Trout; Malachite green; Quechers; Chemistry; Metabolite; Chromatography; Food science; Biology; Fishery; Fish <Actinopterygii>; Biochemistry; Pesticide; Ecology; Pesticide residue","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000301141,0.0004535675,0.0002734298,0.0003236246,0.0002471535,0.0003680577,0.0002354479,0.0004048705,0.0007952554],"category_scores_gemma":[0.0002938364,0.0001733713,0.000318845,0.0002258804,0.0003874641,0.0002305265,0.0003661436,0.0004076291,0.0002807948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004166527,"about_ca_system_score_gemma":0.0004686842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003004323,"about_ca_topic_score_gemma":0.007556189,"domain_scores_codex":[0.9997053,0.00004178916,0.00001004809,0.00008936412,0.0001222253,0.00003127438],"domain_scores_gemma":[0.9998156,0.00003675037,0.00004917921,0.00001846938,0.00006392542,0.00001600185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007926863,0.00000938064,0.001053888,0.0000294618,0.000009908214,0.0000247995,0.00002882865,0.00007181896,0.9972513,0.00001954886,0.00000773403,0.00141398],"study_design_scores_gemma":[0.000005658056,0.0004350767,0.02069659,0.000004600713,0.00002964355,0.0001790144,0.00008461719,0.001104608,0.976859,0.00005369832,0.0005343236,0.00001305692],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827893,0.000592305,0.01526257,0.00004011263,0.0000148856,0.00005111686,0.0002504743,0.00006915458,0.0009300194],"genre_scores_gemma":[0.9845121,0.0006201827,0.01119611,0.0000912752,0.000006793844,0.00006291389,0.0002965213,0.00003812588,0.00317593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003004323,"threshold_uncertainty_score":0.005973637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1283213509092703,"score_gpt":0.3903820417829726,"score_spread":0.2620606908737024,"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."}}