{"id":"W4396592461","doi":"10.1186/s12711-024-00891-w","title":"Redefining and interpreting genomic relationships of metafounders","year":2024,"lang":"en","type":"article","venue":"Genetics Selection Evolution","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Wood Council","funders":"","keywords":"Biology; Evolutionary biology; Selection (genetic algorithm); Genomic selection; Computational biology; Genomics; Data science; Genetics; Genealogy; Genome; Computer science; Artificial intelligence; Genotype; History; Gene; Single-nucleotide polymorphism","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":[0.0002065064,0.00009406548,0.00007384943,0.00008831183,0.00009569189,0.0000218047,0.00005165052,0.0001184358,0.000008936799],"category_scores_gemma":[0.00005457148,0.0001026017,0.00004146837,0.0001381808,0.00007431764,0.00000306407,0.00003174163,0.0001115723,0.000003934945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002905529,"about_ca_system_score_gemma":0.00009885489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009216812,"about_ca_topic_score_gemma":0.00002208044,"domain_scores_codex":[0.9992804,0.00007571719,0.0001919044,0.0002510794,0.00007765115,0.0001232458],"domain_scores_gemma":[0.9997354,0.00002558727,0.00004715886,0.0001034547,0.00005216428,0.00003627381],"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":[0.00006356513,0.00003305889,0.03430825,0.0001281996,0.000139272,1.222387e-7,0.0003800728,0.03714425,0.8889828,0.03049177,0.001011881,0.007316771],"study_design_scores_gemma":[0.001031105,0.002270148,0.6728753,0.0002905287,0.0004422699,0.0001670086,0.0009697373,0.1131406,0.1324308,0.05389516,0.0214065,0.001080901],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6071772,0.00601135,0.3855591,0.00004473771,0.0002467018,0.00008469918,0.000004602977,0.00002316087,0.0008484119],"genre_scores_gemma":[0.9628052,0.00005130382,0.03675929,0.00001502541,0.0001066357,0.000007827912,0.00002222189,0.00001754228,0.0002149796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.756552,"threshold_uncertainty_score":0.4183975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614016411819684,"score_gpt":0.2414092312066697,"score_spread":0.2252690670884729,"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."}}