{"id":"W2161766669","doi":"10.1111/1755-0998.12062","title":"Development of high‐density <scp>SNP</scp> genotyping arrays for white spruce (<i><scp>P</scp>icea glauca</i>) and transferability to subtropical and nordic congeners","year":2013,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Natural Resources Canada; Canadian Forest Service; Université Laval","funders":"Genome Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Biology; SNP genotyping; Genetics; SNP; Genotyping; Single-nucleotide polymorphism; SNP array; Tag SNP; Population; Molecular Inversion Probe; 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":[0.001258312,0.0004994027,0.0006925275,0.0004883717,0.0003226256,0.0006023733,0.0007538799,0.0005135713,0.001509935],"category_scores_gemma":[0.001011191,0.0005339208,0.0006396082,0.0005271318,0.0002241974,0.0003079195,0.0005489698,0.0008885111,0.001087912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002815719,"about_ca_system_score_gemma":0.0006127581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672346,"about_ca_topic_score_gemma":0.004391857,"domain_scores_codex":[0.9990226,0.0001419511,0.00006392682,0.0003042539,0.0003691175,0.00009816823],"domain_scores_gemma":[0.9991054,0.0002259391,0.0001028195,0.0001628611,0.0002999067,0.0001030538],"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":[0.0001131158,0.00005088719,0.002280869,0.0001000242,0.00004073037,0.00005660495,0.00004592761,0.001966042,0.967524,0.0005776233,0.0006395231,0.02660459],"study_design_scores_gemma":[0.0001255055,0.0008227049,0.0509132,0.00004886031,0.0001825137,0.000616405,0.00005629507,0.03327368,0.8790027,0.001011931,0.03383512,0.0001109752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2747547,0.0007913304,0.7060373,0.0002242207,0.0001350722,0.0009739323,0.006228645,0.003333353,0.007521504],"genre_scores_gemma":[0.1843667,0.000548491,0.7923104,0.0002583191,0.0000435544,0.001634239,0.01352074,0.0003272415,0.006990287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001672346,"threshold_uncertainty_score":0.00665468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008179727653547093,"score_gpt":0.2125333712601418,"score_spread":0.2043536436065947,"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."}}