{"id":"W2295715721","doi":"10.1016/j.aquaculture.2016.03.020","title":"Negative genetic correlation between resistance against Piscirickettsia salmonis and harvest weight in coho salmon (Oncorhynchus kisutch)","year":2016,"lang":"en","type":"article","venue":"Aquaculture","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Comisión Nacional de Investigación Científica y Tecnológica; British Council; Government of Canada; Genome British Columbia; Corporación de Fomento de la Producción; Fondo de Fomento al Desarrollo Científico y Tecnológico; Government of the United Kingdom; Universidad de Chile; Genome Canada","keywords":"Biology; Oncorhynchus; Genetic correlation; Genetic variation; Heritability; Selective breeding; Aquaculture; Outbreak; Genetic variability; Population; Zoology; Additive genetic effects; Ecology; Fishery; Genetics; Fish <Actinopterygii>; Demography; Virology; Gene; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000292313,0.0002817363,0.0001502853,0.0006507923,0.0003540829,0.0002974076,0.0002026238,0.0003358416,0.001801692],"category_scores_gemma":[0.0006671695,0.0002225663,0.0001674862,0.00035929,0.0005388855,0.0001532028,0.000295579,0.0004598185,0.0001582608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003350398,"about_ca_system_score_gemma":0.0003776843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006891743,"about_ca_topic_score_gemma":0.0147594,"domain_scores_codex":[0.9997544,0.00004908211,0.00001924468,0.00008826031,0.00004066304,0.00004851853],"domain_scores_gemma":[0.9987878,0.0002810518,0.0004097426,0.00007783285,0.000129658,0.0003139001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005476981,0.0002360122,0.9610426,0.000008790626,0.0001053048,0.0001258149,0.0002341616,0.00005042448,0.03642956,0.00004811446,0.00008603431,0.001085494],"study_design_scores_gemma":[0.000004528772,0.0001212357,0.9992544,0.000001154624,0.00001714245,0.00005809397,0.0001212821,0.00008563555,0.000283231,0.00001396688,0.00003709269,0.000002172175],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998271,0.00001097272,0.00002265721,0.000009716134,0.00000172817,8.398632e-7,0.00002378641,0.000001131091,0.0001021355],"genre_scores_gemma":[0.9996105,0.00001118084,0.00003717445,0.00001360365,0.000001909991,0.000002467572,0.00005960231,0.000001747254,0.0002618778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006891743,"threshold_uncertainty_score":0.01370329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007903279429119173,"score_gpt":0.2178398901771347,"score_spread":0.2099366107480155,"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."}}