{"id":"W1995061033","doi":"10.1186/1471-2164-9-21","title":"Enhancing genetic mapping of complex genomes through the design of highly-multiplexed SNP arrays: application to the large and unsequenced genomes of white spruce and black spruce","year":2008,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Université Laval; Canadian Forest Service; Natural Sciences and Engineering Research Council of Canada","funders":"Genome Canada","keywords":"Biology; SNP genotyping; Genome; Genetics; Black spruce; Genotyping; Single-nucleotide polymorphism; Population; Candidate gene; Reference genome; Synteny; Computational biology; Gene; Genotype; Ecology","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":[0.000170801,0.0001404159,0.0002133412,0.00003355788,0.0001896446,0.000007014519,0.0002427796,0.00009099299,0.000005242071],"category_scores_gemma":[0.00002445133,0.0001075375,0.00005060855,0.0001171038,0.0002400814,0.000004206843,0.0002073639,0.00004842853,9.481374e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009291236,"about_ca_system_score_gemma":0.00006696287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004476095,"about_ca_topic_score_gemma":0.00008714937,"domain_scores_codex":[0.99905,0.00009039429,0.0003322797,0.0002532375,0.0001130919,0.0001610591],"domain_scores_gemma":[0.9991643,0.00004180357,0.0002626621,0.0003777421,0.0001138042,0.00003965485],"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":[0.00005659791,0.00001229227,0.01687348,0.00006716319,0.00004207107,1.709236e-7,0.005769077,0.02346518,0.9533233,0.0000980466,0.00004293841,0.0002497057],"study_design_scores_gemma":[0.001319904,0.0002759326,0.3548636,0.00002520753,0.0001105718,0.00004046085,0.004713022,0.002639577,0.6178443,0.000486134,0.01726637,0.0004149424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8181518,0.001130142,0.1800413,0.00008683388,0.00002205142,0.0004785727,0.00005990316,0.000002840709,0.00002652529],"genre_scores_gemma":[0.9379604,0.0008126571,0.06096365,0.0001186589,0.00004978195,0.000006471438,0.0000303193,0.00001145658,0.00004661235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3379901,"threshold_uncertainty_score":0.4385253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04063927764169348,"score_gpt":0.2433622628649373,"score_spread":0.2027229852232439,"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."}}