{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003179608,0.0003576956,0.0005722771,0.003439017,0.0006044008,0.002723045,0.0008924991,0.0007023203,0.004756051],"category_scores_gemma":[0.01651017,0.0004044092,0.0007286432,0.004132039,0.000777589,0.001760675,0.001301054,0.001265975,0.0008341014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007884311,"about_ca_system_score_gemma":0.000372431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003863411,"about_ca_topic_score_gemma":0.004841498,"domain_scores_codex":[0.9984674,0.0005913534,0.0001047197,0.0005748007,0.0001656841,0.00009599335],"domain_scores_gemma":[0.9877381,0.007064766,0.001796963,0.002017879,0.001069039,0.0003133106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007022063,0.0001034105,0.5708057,0.0005719736,0.0007596028,0.001789519,0.005863414,0.02512768,0.04758772,0.06083252,0.006402402,0.279454],"study_design_scores_gemma":[0.00007367103,0.0001782044,0.5451697,0.0003699884,0.0009558889,0.002112162,0.003399181,0.117343,0.02976757,0.2222748,0.07814085,0.0002150495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6128302,0.001078526,0.3671767,0.0008775502,0.0001430942,0.00005077125,0.006265318,0.002012968,0.009564992],"genre_scores_gemma":[0.8527144,0.0002243785,0.1412491,0.0002920702,0.0000631955,0.00004615798,0.002876005,0.0005003425,0.002034365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004756051,"threshold_uncertainty_score":0.0168156,"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."}}