{"id":"W2121253798","doi":"10.1186/s13059-015-0622-4","title":"Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project","year":2015,"lang":"en","type":"article","venue":"Genome Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":402,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Livestock and Meat Agency; University of Alberta","funders":"National Institute of General Medical Sciences; Biotechnology and Biological Sciences Research Council","keywords":"Biology; Genome; Domestication; Annotation; Phenome; Computational biology; Genome Biology; Human genetics; Evolutionary biology; Genome project; Genomics; Genetics; Gene","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":[0.01219054,0.001576306,0.0008632401,0.002225162,0.00155916,0.00277772,0.001662555,0.001299337,0.01248885],"category_scores_gemma":[0.00581756,0.0003318122,0.001152689,0.00239883,0.00110303,0.001551938,0.005243232,0.003168677,0.003992287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002119264,"about_ca_system_score_gemma":0.01495343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01741338,"about_ca_topic_score_gemma":0.01368683,"domain_scores_codex":[0.9971313,0.001156554,0.00007823244,0.0005191723,0.0005474559,0.0005672314],"domain_scores_gemma":[0.9905563,0.001078255,0.0006108118,0.001109422,0.002101523,0.004543627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003473556,0.000716656,0.02056813,0.001017905,0.0005952815,0.0004910628,0.001607515,0.004200319,0.06242627,0.03207071,0.4713835,0.4014491],"study_design_scores_gemma":[0.0002681759,0.0003798718,0.02901901,0.0001845728,0.0001365933,0.0002642097,0.0005321004,0.003033013,0.008286643,0.00828345,0.949548,0.00006434012],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09011053,0.02756464,0.4066176,0.1314468,0.02068106,0.005521322,0.1324126,0.02076456,0.1648809],"genre_scores_gemma":[0.1384602,0.006521142,0.5458412,0.01783016,0.001359345,0.003386452,0.1956775,0.004092433,0.08683153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01741338,"threshold_uncertainty_score":0.06447047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06304358997357344,"score_gpt":0.3003272641654098,"score_spread":0.2372836741918364,"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."}}