{"id":"W2216178386","doi":"","title":"Genotyping By Sequencing development for Salmo salar: A simulation-based predictive approach using the R package SimRAD.","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Salmo; Genotyping; Computer science; R package; Fishery; Biology; Genotype; Fish <Actinopterygii>; Genetics; Computational science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003787503,0.001565623,0.001635413,0.0009303404,0.0005095213,0.001251952,0.002588506,0.001297595,0.00979122],"category_scores_gemma":[0.007153483,0.0009535975,0.002354345,0.001031967,0.0004583118,0.001117785,0.001215166,0.002124256,0.005063279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006962064,"about_ca_system_score_gemma":0.002057333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006716039,"about_ca_topic_score_gemma":0.006497811,"domain_scores_codex":[0.9990908,0.0004211779,0.00006256091,0.0002182223,0.0001428126,0.00006444649],"domain_scores_gemma":[0.9973226,0.001834151,0.000243483,0.0002386111,0.0002512017,0.0001099948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009244374,0.0003063013,0.02452847,0.003202263,0.00290836,0.0009554263,0.0008724247,0.7020691,0.02059985,0.02950123,0.1097761,0.1043561],"study_design_scores_gemma":[0.0001340895,0.0001370042,0.002396346,0.0001265598,0.0002878121,0.0002049897,0.00008582993,0.9325892,0.004832246,0.01265295,0.04645256,0.0001005017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05006781,0.001696239,0.8109764,0.001029412,0.0004970827,0.0003850378,0.02565069,0.1039633,0.005733904],"genre_scores_gemma":[0.17129,0.001103339,0.774695,0.0007536891,0.000113875,0.001839893,0.02651791,0.02005198,0.003634275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00979122,"threshold_uncertainty_score":0.0327549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159807850554052,"score_gpt":0.2456701904005623,"score_spread":0.2240721118950218,"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."}}