{"id":"W3014404850","doi":"10.1007/s12686-020-01146-8","title":"Development of a massively parallel, genotyping-by-sequencing assay in American badger (Taxidea taxus) highlights the need for careful validation when working with low template DNA","year":2020,"lang":"en","type":"article","venue":"Conservation Genetics Resources","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Birds Canada; Norfolk General Hospital; Ministry of Natural Resources and Forestry; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Badger; Massively parallel; Massive parallel sequencing; Biology; Genotyping; Computational biology; DNA sequencing; Pyrosequencing; Computer science; Genetics; DNA; Parallel computing; Paleontology; Genotype; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001722848,0.0001611194,0.0001761027,0.00004729067,0.0001577646,0.00004504699,0.0002316267,0.0000933042,0.000007126839],"category_scores_gemma":[0.00005772775,0.0001313291,0.00004171317,0.0001900256,0.0001049693,0.000004949345,0.00007030692,0.00006652911,0.000001342962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002599271,"about_ca_system_score_gemma":0.0001283157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000426883,"about_ca_topic_score_gemma":0.0002084523,"domain_scores_codex":[0.9988756,0.00009375657,0.0003393145,0.0003024201,0.000204269,0.0001846041],"domain_scores_gemma":[0.999207,0.00003993049,0.0003476254,0.0001738207,0.0001676945,0.00006389265],"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":[0.0007730564,0.00003287762,0.1510343,0.0001506612,0.000258587,0.000002154064,0.01790995,0.02740278,0.7923613,0.00009466806,0.002637094,0.00734257],"study_design_scores_gemma":[0.001954193,0.0003261363,0.0852742,0.00009861228,0.00007979179,0.000003639392,0.00380102,0.003668147,0.4686541,0.00008714521,0.4354696,0.0005834381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719854,0.0002076582,0.02551496,0.00178726,0.00002995276,0.0003926755,0.00002154604,0.000009441153,0.00005110858],"genre_scores_gemma":[0.9735386,0.00002353354,0.02513545,0.00084645,0.00005820734,0.00002874869,0.0002757054,0.00001783803,0.00007547339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4328325,"threshold_uncertainty_score":0.5355444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03255075030266979,"score_gpt":0.226534116544521,"score_spread":0.1939833662418512,"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."}}