{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002900969,0.0001226313,0.0002305482,0.00002335872,0.00006140047,0.00001496882,0.0001374401,0.00005988093,0.000005537606],"category_scores_gemma":[0.00002952603,0.00006774625,0.00002790214,0.00006949892,0.00006280563,0.00003365196,0.0001480886,0.00004197337,0.000002736306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006775962,"about_ca_system_score_gemma":0.00001370779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004408634,"about_ca_topic_score_gemma":0.01340663,"domain_scores_codex":[0.9989241,0.00002955531,0.0004673983,0.0002873426,0.00009925167,0.0001923391],"domain_scores_gemma":[0.9995748,0.0001038909,0.0001813938,0.00007752625,0.00002329005,0.00003903754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000363964,0.00007074746,0.1753857,0.00005654857,0.000006790941,9.147297e-8,0.0002992378,0.0001491971,0.8174406,0.00001369071,5.50262e-7,0.006540494],"study_design_scores_gemma":[0.0002553061,0.000126112,0.9706983,0.00001005244,0.000007709471,3.413257e-7,0.0002417077,0.00006069083,0.02797992,0.0002044879,0.0002918918,0.0001234901],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988191,0.0001484256,0.0005185661,0.00003090374,0.00002828236,0.0004187344,0.00002398649,0.000003714865,0.000008337362],"genre_scores_gemma":[0.9914541,0.0001319271,0.008248587,0.00002161659,0.000016605,0.00003734446,0.00004885833,0.000001704516,0.00003930696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7953126,"threshold_uncertainty_score":0.7481213,"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."}}