{"id":"W2033312145","doi":"10.1371/journal.pone.0081992","title":"Genomic DNA Enrichment Using Sequence Capture Microarrays: a Novel Approach to Discover Sequence Nucleotide Polymorphisms (SNP) in Brassica napus L","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Plant Disease Resistance and Genetics","field":"Agricultural and Biological Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Plant Biotechnology Institute; National Research Council Canada; Agriculture and Agri-Food Canada","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria","keywords":"Biology; Genetics; Single-nucleotide polymorphism; SNP genotyping; Genotyping; Genome; DNA sequencing; Genetic variation; Sequence analysis; DNA microarray; Genotype; Computational biology; DNA; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002936798,0.0006611714,0.0004540936,0.0005284054,0.0002638361,0.0003853313,0.0005667515,0.0006070214,0.0008309908],"category_scores_gemma":[0.0002688953,0.0003853907,0.0003384341,0.000387194,0.0002166333,0.000277055,0.0003704067,0.0005406262,0.0005983682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003703363,"about_ca_system_score_gemma":0.000220594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001146292,"about_ca_topic_score_gemma":0.003226586,"domain_scores_codex":[0.9995198,0.00005166002,0.00001414946,0.0002038454,0.0001586879,0.00005176052],"domain_scores_gemma":[0.9998637,0.00004233983,0.00003607162,0.00001367183,0.00002765343,0.00001647776],"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":[0.00002015449,0.000006068381,0.0002120052,0.00003655729,0.000005182667,0.00001194275,0.00001072933,0.0000894872,0.9962401,0.00003469162,0.00005528389,0.003277684],"study_design_scores_gemma":[0.00002053388,0.0003686989,0.0136347,0.0000149021,0.00004658393,0.0005051315,0.00005381732,0.007209163,0.9686232,0.0002277742,0.009254665,0.00004084163],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7120288,0.005659814,0.2691473,0.0008781278,0.0001674862,0.0003943142,0.00433081,0.002307606,0.005085797],"genre_scores_gemma":[0.7033224,0.003624767,0.2746431,0.001049726,0.0001114945,0.0007371911,0.005319492,0.0001286828,0.01106311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001146292,"threshold_uncertainty_score":0.002779901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08048676020632324,"score_gpt":0.2264375338952787,"score_spread":0.1459507736889555,"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."}}