{"id":"W2115610250","doi":"10.1038/nmeth.1185","title":"SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries","year":2008,"lang":"en","type":"article","venue":"Nature Methods","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":676,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Genetics; Biology; Single-nucleotide polymorphism; Genotyping; SNP genotyping; Allele frequency; Genome; Genotype; DNA sequencing; SNP; Deep sequencing; Allele; Population; Computational biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001608452,0.0001042186,0.0001308405,0.0000258269,0.00006998863,0.00001256797,0.00009589717,0.0002695189,0.000007255516],"category_scores_gemma":[0.0003314346,0.00009587218,0.00003864302,0.000080937,0.0001320579,0.00001627252,0.0000459912,0.000150355,2.212897e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006642182,"about_ca_system_score_gemma":0.00006564089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001643259,"about_ca_topic_score_gemma":0.000001536462,"domain_scores_codex":[0.9991984,0.0001736131,0.0001750063,0.0002514198,0.00009295257,0.0001085446],"domain_scores_gemma":[0.999548,0.00005170057,0.0000966911,0.0002200155,0.00004557235,0.00003805828],"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":[0.00003801937,0.00001796787,0.001219445,0.00002457236,0.00003656197,3.671456e-7,0.0003779409,0.0002842507,0.9796881,0.004988744,0.00108857,0.01223547],"study_design_scores_gemma":[0.0002754158,0.0001708652,0.0235441,0.000008859985,0.0000234226,0.00003278503,0.0001093415,0.000163706,0.9550329,0.02001459,0.0004734886,0.0001504878],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5334649,0.005962585,0.4592314,0.00005679085,0.0001085879,0.00009731095,0.000008878787,0.000007771871,0.00106173],"genre_scores_gemma":[0.4463899,0.00006615397,0.5531114,0.00005686506,0.00004990474,0.000005099246,0.00009117753,0.000007845619,0.0002216835],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09387993,"threshold_uncertainty_score":0.3909554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02242832749851655,"score_gpt":0.3323102235550311,"score_spread":0.3098818960565146,"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."}}