{"id":"W1990016126","doi":"10.1021/jf103241y","title":"Interlaboratory Evaluation of a Real-Time Multiplex Polymerase Chain Reaction Method for Identification of Salmon and Trout Species in Commercial Products","year":2011,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"U.S. Food and Drug Administration; Oregon State University; California Department of Fish and Wildlife; Massachusetts Department of Fish and Game","keywords":"Trout; Polymerase chain reaction; Species identification; Multiplex polymerase chain reaction; Fishery; Identification (biology); Multiplex; Biology; Real-time polymerase chain reaction; Fish <Actinopterygii>; Zoology; Ecology; Bioinformatics; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0007739844,0.00008747924,0.0001695578,0.00004046941,0.00002750776,0.000009417752,0.00007444534,0.00009387321,0.000004563466],"category_scores_gemma":[0.0002236983,0.00006704639,0.00005010749,0.00009790461,0.00005904532,0.00002000634,0.00001649286,0.00005746236,9.718826e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001586787,"about_ca_system_score_gemma":0.00004354615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008271386,"about_ca_topic_score_gemma":0.000006098975,"domain_scores_codex":[0.9990048,0.00006999946,0.0005583401,0.0001492802,0.0001507691,0.00006674128],"domain_scores_gemma":[0.9982257,0.00001567498,0.0007530015,0.0001039992,0.0008672606,0.00003439745],"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":[0.0001437191,0.0001206632,0.000504754,0.000103247,0.00004591064,3.065261e-8,0.0004742194,0.000002359954,0.9968289,0.00001958482,0.0001227767,0.001633878],"study_design_scores_gemma":[0.0006389374,0.0001457113,0.1771409,0.00003322653,0.00006301553,0.00001721266,0.0008119622,0.00003856949,0.8209927,0.00001574225,0.00003756458,0.00006446594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989736,0.0004313966,0.0001281278,0.0001062738,0.00006437113,0.0001730283,0.00003307923,0.000001740033,0.00008837609],"genre_scores_gemma":[0.9986,0.0001795092,0.0008948038,0.000003549079,0.0001107997,0.00001058605,0.00007158879,0.000004776059,0.0001243823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1766361,"threshold_uncertainty_score":0.2734073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03805484994076669,"score_gpt":0.2835343147384567,"score_spread":0.2454794647976901,"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."}}