{"id":"W7015267595","doi":"","title":"Single vs. Pooled: Metabarcoding Based Species Misrepresentation Detection of Sushi in Ontario by Sample Pooling Compared to Conventional DNA Barcoding","year":2022,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"DNA barcoding; Pooling; Sample (material); Misrepresentation; Identification (biology); Barcode","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035618,0.0001354834,0.00022688,0.000243349,0.0002316134,0.00001874184,0.0003666821,0.0001057169,0.0005541681],"category_scores_gemma":[0.00009207637,0.00017031,0.0001781766,0.0002727438,0.00005835211,0.00001372472,0.00006414049,0.0001629084,0.000003649124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001289684,"about_ca_system_score_gemma":0.0001480411,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01406369,"about_ca_topic_score_gemma":0.06803246,"domain_scores_codex":[0.9988147,0.0001474899,0.0002859542,0.0003232796,0.0002916453,0.000136927],"domain_scores_gemma":[0.9989487,0.00006576372,0.0004249782,0.0003095015,0.0002109593,0.00004011252],"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":[0.0004940307,0.00009288614,0.0007080102,0.00005123826,0.00007693937,3.401896e-7,0.0009093247,0.0004889914,0.9963568,0.00008990404,0.0005858808,0.0001456194],"study_design_scores_gemma":[0.001038986,0.0001395486,0.1442064,0.00005002821,0.0002134814,0.000001136061,0.01585352,0.0003671268,0.8147544,0.00003402526,0.02304914,0.0002921193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946733,0.000120814,0.003695626,0.0001961661,0.0003302165,0.0003266381,0.0001507544,0.000009195765,0.0004973069],"genre_scores_gemma":[0.9879398,0.00001600828,0.0003279353,0.00002112637,0.0000219198,0.000002728733,0.006386353,0.00001464815,0.005269523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1816024,"threshold_uncertainty_score":0.9925017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03126453840975011,"score_gpt":0.2486214580585918,"score_spread":0.2173569196488417,"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."}}