{"id":"W3007506343","doi":"10.3389/fgene.2020.00067","title":"NanoGBS: A Miniaturized Procedure for GBS Library Preparation","year":2020,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Genome Canada","keywords":"Genotyping; SNP genotyping; Multiplexing; Single-nucleotide polymorphism; SNP; DNA sequencing; Ion semiconductor sequencing; Computational biology; Computer science; Throughput; Biology; Genotype; Genetics; DNA; Operating system; Gene; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"protocol","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002242649,0.001689773,0.001663302,0.002691374,0.0009404822,0.001524704,0.001934867,0.001147477,0.01163244],"category_scores_gemma":[0.002700901,0.001513586,0.001133588,0.00132613,0.0008620261,0.0008941917,0.002178327,0.002586939,0.01428343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004792851,"about_ca_system_score_gemma":0.00101907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000734282,"about_ca_topic_score_gemma":0.002340663,"domain_scores_codex":[0.9975454,0.000428691,0.0002021425,0.0006483995,0.0009779707,0.0001972894],"domain_scores_gemma":[0.9986424,0.0003606133,0.000141865,0.0004806377,0.0002233328,0.0001511041],"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":[0.0001967674,0.0001273611,0.0006218266,0.0004718647,0.00008603199,0.0002039811,0.0002235189,0.0006779911,0.9246962,0.001700144,0.01135583,0.05963859],"study_design_scores_gemma":[0.00007523524,0.0002844523,0.003062183,0.000097213,0.00007199743,0.000835349,0.00007943167,0.005080026,0.7930362,0.001683625,0.1955458,0.0001483651],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02747291,0.001905355,0.9341826,0.0004866931,0.0007021037,0.00225989,0.008815134,0.01765618,0.006519049],"genre_scores_gemma":[0.04158684,0.001836704,0.9086418,0.001003182,0.0001318647,0.006046664,0.02220716,0.003365891,0.01517994],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01163244,"threshold_uncertainty_score":0.03891438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009611726642234423,"score_gpt":0.2240070096455244,"score_spread":0.21439528300329,"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."}}