{"id":"W2727305748","doi":"10.1186/s12864-017-3873-5","title":"LinkImputeR: user-guided genotype calling and imputation for non-model organisms","year":2017,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canada Research Chairs; Genome Canada","keywords":"Imputation (statistics); Genotype; Missing data; Genotyping; Biology; Software; Computational biology; DNA microarray; Data quality; Genomics; Genome; Data mining; Computer science; Genetics; Statistics; Gene; Machine learning; Mathematics","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":[0.005764057,0.002514966,0.001791608,0.002442971,0.001283139,0.003051274,0.00736204,0.002515486,0.02312576],"category_scores_gemma":[0.01824958,0.002200931,0.002754201,0.001973364,0.001163733,0.002715294,0.004376829,0.004541505,0.01588281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008787744,"about_ca_system_score_gemma":0.001937418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001876328,"about_ca_topic_score_gemma":0.00270458,"domain_scores_codex":[0.9976906,0.0004598668,0.0001953651,0.0007041291,0.0007950228,0.0001550245],"domain_scores_gemma":[0.993473,0.003727119,0.0007398197,0.001220032,0.0005453101,0.0002947892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003494949,0.001263294,0.0239705,0.003518781,0.002792818,0.001828355,0.002049844,0.06352875,0.03899235,0.02018102,0.4807866,0.3575929],"study_design_scores_gemma":[0.001277327,0.0004393623,0.00950041,0.0005316878,0.000574885,0.001037073,0.0001719742,0.6630585,0.07798295,0.04132996,0.2033258,0.0007701055],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.007411925,0.0002375276,0.4773108,0.0002630145,0.0002192762,0.0002392789,0.009987496,0.5020258,0.002304819],"genre_scores_gemma":[0.05659488,0.0004585466,0.7638776,0.0008842953,0.0001589693,0.002959487,0.04115235,0.1269086,0.007005366],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02312576,"threshold_uncertainty_score":0.07736337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03069512069075372,"score_gpt":0.29683713121111,"score_spread":0.2661420105203563,"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."}}