{"id":"W4408187354","doi":"10.1093/genetics/iyaf027","title":"The Unified Phenotype Ontology : a framework for cross-species integrative phenomics","year":2025,"lang":"en","type":"article","venue":"Genetics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Basic Energy Sciences; Takeda Canada; Biotechnology and Biological Sciences Research Council; Office of Science; National Institutes of Health; Norges Idrettshøgskole; GlaxoSmithKline foundation; National Human Genome Research Institute; Wellcome Trust; Eunice Kennedy Shriver National Institute of Child Health and Human Development; U.S. Department of Energy; European Bioinformatics Institute; Centers for Disease Control and Prevention; Sanofi Australia; Biogen; Celgene; Office of the Director","keywords":"Phenomics; Ontology; Phenome; Biology; Data integration; Phenotypic trait; Controlled vocabulary; Computational biology; Open Biomedical Ontologies; Representation (politics); Biological data; Data science; Organism; Computer science; Vocabulary; Phenotype; Ontology-based data integration; Bioinformatics; Genomics; Data mining; Information retrieval; Genetics; Genome; Ontology alignment; Semantic Web; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001809521,0.0001505594,0.00015216,0.00002322076,0.0002924772,0.00006387584,0.0004112632,0.0003203083,0.000005353932],"category_scores_gemma":[0.0009040038,0.0001017107,0.00009385845,0.00009765544,0.0005871125,6.653185e-7,0.00015301,0.0001415568,0.000003948273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001794161,"about_ca_system_score_gemma":0.0001473095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000300365,"about_ca_topic_score_gemma":0.0002102859,"domain_scores_codex":[0.9990843,0.00004740384,0.0002152893,0.0002846183,0.00006210829,0.0003063095],"domain_scores_gemma":[0.9990743,0.0002555783,0.00006818205,0.0004086161,0.0001512821,0.00004207006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001598288,0.0002217425,0.01342418,0.0001047485,0.0009350665,0.000003163686,0.001074919,0.0002435718,0.06854641,0.3679777,0.08352295,0.4623472],"study_design_scores_gemma":[0.0004525069,0.0003444758,0.00605906,0.00001887113,0.00003082884,0.000001514045,0.0006668288,0.0002148783,0.02732632,0.04373644,0.9209728,0.000175436],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.345285,0.01439872,0.6275365,0.004486503,0.002142566,0.000572876,0.00008386813,0.00006137198,0.005432575],"genre_scores_gemma":[0.8960446,0.001618421,0.08675252,0.001609609,0.000619502,0.0001432211,0.00007688061,0.00003052087,0.01310469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8374499,"threshold_uncertainty_score":0.4147642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122785670023918,"score_gpt":0.3328977548537405,"score_spread":0.3116698981535013,"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."}}