{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001397815,0.0000798069,0.0000853665,0.00003165361,0.00005147135,0.0000503201,0.0001509161,0.00004601003,0.000002474816],"category_scores_gemma":[0.00002774075,0.0000723757,0.00004878748,0.00001551451,0.00002009919,0.00001253222,0.00007837841,0.00005492055,0.000002052729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003931948,"about_ca_system_score_gemma":0.00007721388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005466893,"about_ca_topic_score_gemma":0.000007015244,"domain_scores_codex":[0.9994612,0.000015384,0.0002280276,0.00008394688,0.0001047002,0.0001067757],"domain_scores_gemma":[0.9995526,0.00001481335,0.0001783606,0.00005935461,0.0001502996,0.00004455576],"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":[0.00002747419,0.00002225057,0.001319492,0.000002715264,0.0001517615,0.000001439257,0.0002145027,0.0001944763,0.995049,0.001849131,0.0003659985,0.0008017498],"study_design_scores_gemma":[0.0009282832,0.0001979094,0.003224355,0.00002213079,0.000096886,0.001283373,0.0006809807,0.0005681304,0.5704672,0.0008187057,0.4213292,0.0003829084],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839666,0.007399312,0.007502242,0.0001713596,0.0006017705,0.00007085098,0.0001232112,7.344574e-7,0.000163866],"genre_scores_gemma":[0.9900033,0.005119694,0.002193297,0.0002458218,0.002298625,0.000004512297,0.00005760595,0.000008944046,0.00006822148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4245819,"threshold_uncertainty_score":0.2951396,"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."}}