{"id":"W2006192575","doi":"10.1186/1471-2164-15-708","title":"Genome wide SNP identification in chickpea for use in development of a high density genetic map and improvement of chickpea reference genome assembly","year":2014,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Plant Biotechnology Institute; Saskatchewan Research Council (Canada); University of Saskatchewan","funders":"Agriculture and Agri-Food Canada; Saskatchewan Pulse Growers","keywords":"Biology; Genetics; Single-nucleotide polymorphism; Tag SNP; Genotyping; Genome; SNP genotyping; Reference genome; Population; Molecular Inversion Probe; SNP array; DNA sequencing; Sequence assembly; Genotype; Gene; Transcriptome","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":[0.001384991,0.0006544162,0.0006897762,0.001327733,0.0006662583,0.0008083505,0.0007043043,0.0006572886,0.001721643],"category_scores_gemma":[0.001514688,0.0004265814,0.0009134023,0.00142075,0.0001905715,0.0002959732,0.0005418577,0.0008529843,0.001285053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005808502,"about_ca_system_score_gemma":0.0008056801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005696393,"about_ca_topic_score_gemma":0.01039953,"domain_scores_codex":[0.9991291,0.0001177442,0.00004980677,0.0004267196,0.0002141365,0.00006244583],"domain_scores_gemma":[0.9992129,0.0001451431,0.0001241217,0.0001591908,0.0003123253,0.00004633468],"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":[0.0006136582,0.00009241527,0.02096039,0.0007518387,0.0003473931,0.0005403637,0.0007727637,0.006132079,0.8947635,0.00176953,0.00343227,0.06982379],"study_design_scores_gemma":[0.0002180111,0.0005218388,0.3587203,0.0003928197,0.001087347,0.00197955,0.000468665,0.05702285,0.4577227,0.002644178,0.1190438,0.0001780139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5780391,0.005626529,0.3669432,0.0003482964,0.0002584693,0.0004162595,0.03681859,0.004480093,0.007069346],"genre_scores_gemma":[0.4167449,0.001426907,0.5175776,0.0002385585,0.0000341127,0.0005990103,0.05754431,0.0007326864,0.005101883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005696393,"threshold_uncertainty_score":0.01132643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366582100240382,"score_gpt":0.2057561870395478,"score_spread":0.1690979770155096,"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."}}