{"id":"W2999855058","doi":"10.3390/separations7010005","title":"Profiling Volatilomes: A Novel Forensic Method for Identification of Confiscated Illegal Wildlife Items","year":2020,"lang":"en","type":"article","venue":"Separations","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"United States Agency for International Development","keywords":"Wildlife; Profiling (computer programming); African elephant; Forensic identification; DNA profiling; Multiplex; Biology; Wildlife trade; Computer science; Ecology; Bioinformatics; DNA","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":[],"consensus_categories":[],"category_scores_codex":[0.0002490378,0.00011155,0.0001432675,0.00005393528,0.0001343092,0.00004136042,0.0001611976,0.0001026963,0.00001357909],"category_scores_gemma":[0.0004088618,0.0001190822,0.0001143708,0.0002314936,0.00006215451,0.0000118888,0.00002296797,0.00004879397,0.00001748231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006776936,"about_ca_system_score_gemma":0.0001120553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000388635,"about_ca_topic_score_gemma":0.00000795895,"domain_scores_codex":[0.9988241,0.00004009981,0.0005428133,0.0003460037,0.0001211466,0.0001257937],"domain_scores_gemma":[0.9987894,0.00003272853,0.0003059072,0.0003029854,0.0004972303,0.00007172277],"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":[0.00004564572,0.00005713676,0.0001146526,0.00003678409,0.00005723569,1.587526e-8,0.0002136751,0.0006152204,0.9764375,0.01282444,0.009438242,0.0001594367],"study_design_scores_gemma":[0.0005965953,0.0001194207,0.0004765518,0.000005202778,0.00005179949,0.000002251125,0.0003266304,0.05414389,0.8748658,0.00006845048,0.0691776,0.000165803],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05054609,0.00007649227,0.9443836,0.003038883,0.0002239139,0.0008528272,0.0003636433,0.00003604222,0.0004784662],"genre_scores_gemma":[0.9687955,0.00001009876,0.02692942,0.0005563287,0.0001848782,0.0002042458,0.002113425,0.00002346262,0.001182612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9182494,"threshold_uncertainty_score":0.4856032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04978772072514071,"score_gpt":0.3435458481638489,"score_spread":0.2937581274387082,"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."}}