{"id":"W2949819089","doi":"10.1186/s12864-018-4611-3","title":"A Sequel to Sanger: amplicon sequencing that scales","year":2018,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":295,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund; Ontario Ministry of Research, Innovation and Science","keywords":"Sanger sequencing; Amplicon; Biology; Computational biology; DNA sequencer; DNA sequencing; Genetics; Amplicon sequencing; Ion semiconductor sequencing; Massive parallel sequencing; Mitochondrial DNA; Polymerase chain reaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01041846,0.002175313,0.001890821,0.002497329,0.001139623,0.002842956,0.002381306,0.002722607,0.02220207],"category_scores_gemma":[0.02067446,0.002199954,0.001858989,0.001503256,0.001917628,0.003373049,0.003605593,0.005619829,0.02365082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007655906,"about_ca_system_score_gemma":0.001470344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006435083,"about_ca_topic_score_gemma":0.001139504,"domain_scores_codex":[0.989498,0.004179649,0.0007566183,0.002406758,0.002768096,0.000390922],"domain_scores_gemma":[0.9857079,0.005675806,0.001215064,0.004866864,0.001924035,0.000610344],"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":[0.001061637,0.0003662932,0.004221541,0.003079915,0.000726093,0.0009328618,0.0012443,0.004457932,0.4559217,0.04723344,0.1239412,0.3568131],"study_design_scores_gemma":[0.0001104831,0.0009114465,0.002940028,0.000596125,0.0002939291,0.002590337,0.0002038923,0.02253605,0.3006895,0.02561728,0.6431784,0.0003325838],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008013079,0.003975569,0.9359519,0.002426694,0.003692805,0.0006327415,0.002446662,0.02622068,0.01663978],"genre_scores_gemma":[0.02258023,0.003263519,0.942241,0.002433566,0.001029233,0.001382993,0.004105575,0.00636705,0.01659696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02220207,"threshold_uncertainty_score":0.07427335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402932936420695,"score_gpt":0.28763935900217,"score_spread":0.253610029637963,"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."}}