{"id":"W4382517305","doi":"10.1101/2023.06.27.546670","title":"The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China; Agricultural Research Service; Jiangsu Agriculture Research System; National Institute of Food and Agriculture; Chinese Academy of Sciences; National Natural Science Foundation of China; U.S. Department of Agriculture","keywords":"Biology; Genome; Genetics; Functional genomics; Gene; Genomics; Computational biology; Regulatory sequence; Context (archaeology); Expression quantitative trait loci; Polyadenylation; Whole genome sequencing; Regulation of gene expression; Gene expression; Single-nucleotide polymorphism; Genotype","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":[0.001122794,0.0004695014,0.0004821732,0.001072367,0.0004078464,0.0005631899,0.0004272649,0.0003240251,0.004627587],"category_scores_gemma":[0.001726523,0.0002633583,0.0005570456,0.0009967791,0.0002275672,0.0001737438,0.0008137969,0.0003800946,0.001672893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001990874,"about_ca_system_score_gemma":0.0004135449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002911414,"about_ca_topic_score_gemma":0.005481314,"domain_scores_codex":[0.9992866,0.0001110091,0.0000464761,0.0003721307,0.0001330459,0.00005076429],"domain_scores_gemma":[0.9989269,0.0004282863,0.0001183313,0.0002617716,0.0001986323,0.00006595052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002748754,0.0001405737,0.1312364,0.001434944,0.0008136705,0.001856146,0.00113776,0.008007372,0.6887495,0.00276004,0.05109663,0.1100183],"study_design_scores_gemma":[0.0003114871,0.0006149777,0.5664386,0.0003674386,0.001067731,0.003381144,0.0006243412,0.01552095,0.1294617,0.003124919,0.2789305,0.0001562687],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6523516,0.002298765,0.06998765,0.0003049279,0.0002910907,0.0001662898,0.257422,0.007054533,0.01012306],"genre_scores_gemma":[0.4391869,0.0005910958,0.0840078,0.0005578824,0.00009481988,0.0004734235,0.4627199,0.003986561,0.008381611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004627587,"threshold_uncertainty_score":0.01548082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02355158485356696,"score_gpt":0.2574272795022766,"score_spread":0.2338756946487097,"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."}}