{"id":"W2606522509","doi":"10.1101/116814","title":"Base Composition, Speciation, and Why the Mitochondrial Barcode Precisely Classifies","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University","keywords":"Biology; Sympatric speciation; Reproductive isolation; Mitochondrial DNA; Barcode; Evolutionary biology; Genome; Genetic algorithm; Genetics; Nuclear gene; DNA barcoding; Gene; Computational biology","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":[0.0005896824,0.000207878,0.000277917,0.0005094587,0.0004941176,0.0008606751,0.0004000939,0.00113504,0.001094147],"category_scores_gemma":[0.00188667,0.0002050159,0.0001412207,0.0003934497,0.00129704,0.001441348,0.0003575716,0.0008599718,0.0007772608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000374816,"about_ca_system_score_gemma":0.0002188779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006569736,"about_ca_topic_score_gemma":0.0007704253,"domain_scores_codex":[0.9995603,0.00009284647,0.00002912416,0.0001563634,0.0001070341,0.00005438459],"domain_scores_gemma":[0.999111,0.0001716727,0.0002636547,0.0001482883,0.0002000898,0.0001052603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001812245,0.00002586581,0.01045234,0.0001122643,0.00002051069,0.0002344581,0.0003208571,0.0004699302,0.9601868,0.01031622,0.0003356213,0.01734401],"study_design_scores_gemma":[0.00001930607,0.0002293819,0.06585954,0.0001090677,0.00005515535,0.00264378,0.0007760595,0.01093659,0.8737743,0.02196724,0.02352552,0.0001041289],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9298365,0.003757812,0.05758171,0.001928616,0.0004611765,0.00002527594,0.0003785254,0.0003143864,0.005715911],"genre_scores_gemma":[0.985051,0.0005461645,0.01202631,0.0002356719,0.00006524767,0.000007122481,0.0001740305,0.00008851708,0.001805766],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00113504,"threshold_uncertainty_score":0.003660262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548045435944461,"score_gpt":0.2186718940826602,"score_spread":0.2031914397232156,"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."}}