{"id":"W2081046556","doi":"10.1155/2012/831460","title":"SNP Discovery through Next-Generation Sequencing and Its Applications","year":2012,"lang":"en","type":"article","venue":"International Journal of Plant Genomics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":314,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Vineland Research and Innovation Centre; University of Manitoba","funders":"Genome Canada","keywords":"SNP; Computer science; DNA sequencing; Computational biology; Selection (genetic algorithm); Single-nucleotide polymorphism; Software; Key (lock); Tag SNP; Biology; Genetics; Machine learning; Gene; Genotype","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":[0.006553704,0.0006535374,0.001425865,0.003401376,0.0006023105,0.002012151,0.001066195,0.001524071,0.003463341],"category_scores_gemma":[0.01038456,0.0006096669,0.001065754,0.006362172,0.0004626049,0.001205672,0.001086736,0.001312325,0.002095615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005800464,"about_ca_system_score_gemma":0.001191311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278445,"about_ca_topic_score_gemma":0.001368006,"domain_scores_codex":[0.9966137,0.001682193,0.0002488944,0.0005616327,0.0008133009,0.00008028277],"domain_scores_gemma":[0.9933035,0.00492695,0.0004029902,0.0004496289,0.0007733991,0.0001436245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003043438,0.00007967014,0.01050408,0.00299663,0.0005114138,0.0006828975,0.0003414521,0.0117018,0.04113593,0.02171786,0.01549421,0.8945297],"study_design_scores_gemma":[0.0001728382,0.0005055195,0.0327163,0.002238631,0.0009297821,0.005073261,0.0004596383,0.1690482,0.1004749,0.1955976,0.4923278,0.0004555155],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0222461,0.04306994,0.9075968,0.003530171,0.0007064397,0.0003933002,0.006351204,0.00569834,0.01040769],"genre_scores_gemma":[0.05303603,0.02951207,0.9069163,0.001062671,0.0004298417,0.000584615,0.005334265,0.0003570813,0.002767133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006553704,"threshold_uncertainty_score":0.03465974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06415091237072831,"score_gpt":0.2779683454940851,"score_spread":0.2138174331233568,"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."}}