{"id":"W2171497898","doi":"10.1155/2012/628204","title":"Screen for Footprints of Selection during Domestication/Captive Breeding of Atlantic Salmon","year":2012,"lang":"en","type":"article","venue":"Comparative and Functional Genomics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"European Social Fund; National Cancer Institute; Academy of Finland; Eesti Teadusfondi","keywords":"Domestication; Biology; Salmo; Selection (genetic algorithm); Microsatellite; Evolutionary biology; Adaptation (eye); Genetic variation; Selective sweep; Single-nucleotide polymorphism; Centimorgan; Genetics; Haplotype; Allele; Fishery; Gene; Fish <Actinopterygii>; Gene mapping; Genotype; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007688835,0.00007630305,0.0001213753,0.00002928037,0.00005822455,0.000002648609,0.00003598834,0.00005030009,0.00000854878],"category_scores_gemma":[0.0000192538,0.00007567579,0.00003463282,0.00004515819,0.00008008325,0.000004231217,0.00003107259,0.00003043873,8.544181e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008660671,"about_ca_system_score_gemma":0.00003219114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006144769,"about_ca_topic_score_gemma":0.000002577523,"domain_scores_codex":[0.9995556,0.00001521915,0.0001557074,0.0001211906,0.00004825688,0.0001040228],"domain_scores_gemma":[0.9996148,0.00003164873,0.00010187,0.00006118433,0.0001498288,0.00004063833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005966956,0.0001124887,0.1004987,0.0000571878,0.0001634827,5.091926e-9,0.0004324884,0.001842874,0.8759643,0.0198738,0.0001782568,0.0002796827],"study_design_scores_gemma":[0.000498566,0.0003409128,0.8308723,0.000008608712,0.00004004402,0.000007802293,0.0002118171,0.0001021253,0.1663511,0.0006536937,0.0008173595,0.00009563995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316027,0.0004792722,0.06722558,0.000006907267,0.00008921119,0.0001627765,0.0000208206,0.000002139,0.0004105977],"genre_scores_gemma":[0.985971,0.00001892803,0.01355982,0.000006790357,0.0002409611,0.00001341478,0.00005976818,0.00000597275,0.0001232788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7303736,"threshold_uncertainty_score":0.3085969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04220169227100896,"score_gpt":0.2707667144392137,"score_spread":0.2285650221682048,"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."}}