{"id":"W6966900289","doi":"10.5061/dryad.53b58","title":"Data from: A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: testing co-localization among outlier markers, candidate genes, and QTLs for production traits","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Guelph","funders":"","keywords":"Genome Scan; Candidate gene; Domestication; Genome; Population; Quantitative trait locus; Locus (genetics); Selection (genetic algorithm); Founder effect; Identification (biology)","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":[0.001544916,0.001485493,0.001259806,0.002206326,0.0007811844,0.00149804,0.002047754,0.001597299,0.02650201],"category_scores_gemma":[0.005277272,0.0006630907,0.001235208,0.003582515,0.0004526335,0.0007170294,0.002111316,0.001296486,0.0159626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009857269,"about_ca_system_score_gemma":0.0021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02883559,"about_ca_topic_score_gemma":0.05862474,"domain_scores_codex":[0.9990603,0.0001320939,0.0001450668,0.0003339188,0.0002015899,0.0001269642],"domain_scores_gemma":[0.9978864,0.000681319,0.0003612938,0.0004153338,0.0004325209,0.0002231933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006764316,0.0001047652,0.01750083,0.003510434,0.0004211683,0.0002208222,0.0003185212,0.001143353,0.003139358,0.001014533,0.9635535,0.008396254],"study_design_scores_gemma":[0.001500917,0.00009606987,0.0876525,0.0005991917,0.0002743918,0.0002281164,0.0003264901,0.001489847,0.002515235,0.002132629,0.9030665,0.0001180908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009898861,0.00004453797,0.0001223246,0.00004900579,0.00001130835,0.00001419674,0.9982111,0.0002845355,0.0002730122],"genre_scores_gemma":[0.001446707,0.00003123521,0.0005028644,0.00002322039,0.000003137713,0.00008092762,0.9975853,0.00007852359,0.0002479382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02883559,"threshold_uncertainty_score":0.08865809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05368588498571369,"score_gpt":0.2981720185579527,"score_spread":0.244486133572239,"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."}}