{"id":"W192939834","doi":"10.4137/bbi.s451","title":"Ontologies for Bioinformatics","year":2008,"lang":"en","type":"article","venue":"Bioinformatics and Biology Insights","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Interoperability; Computer science; Ontology; Data science; Context (archaeology); Semantic interoperability; Open Biomedical Ontologies; Semantics (computer science); Semantic Web; Meaning (existential); IDEF5; Semantic integration; World Wide Web; Knowledge management; Upper ontology; Semantic Web Stack; Ontology alignment; Biology","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":[0.008681783,0.001556481,0.001946733,0.006153908,0.003645542,0.01108777,0.004062039,0.005284216,0.01464611],"category_scores_gemma":[0.02035593,0.0009603506,0.002375482,0.009236624,0.006362775,0.01664886,0.006783286,0.006903969,0.01012719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003960345,"about_ca_system_score_gemma":0.007109116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005404662,"about_ca_topic_score_gemma":0.003733021,"domain_scores_codex":[0.9916852,0.003673137,0.001052437,0.0010872,0.002104476,0.0003975446],"domain_scores_gemma":[0.9896713,0.005136354,0.0007007119,0.002319098,0.001557945,0.0006146054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001928399,0.00002401644,0.000168425,0.0007323689,0.00004818825,0.0001484886,0.0004870893,0.001527874,0.0003000005,0.864491,0.0440271,0.08802614],"study_design_scores_gemma":[0.000007647915,0.000004579409,0.00006959586,0.0004041079,0.00001198293,0.0001323263,0.0001373687,0.001906909,0.0001002118,0.730413,0.2667966,0.00001559023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001577862,0.07355103,0.7416415,0.04609925,0.004655702,0.0005709061,0.003785754,0.0058192,0.1222988],"genre_scores_gemma":[0.04762332,0.06526709,0.8346211,0.01224613,0.004798245,0.001142625,0.0088894,0.001122143,0.02428993],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01464611,"threshold_uncertainty_score":0.04899615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05290572275187795,"score_gpt":0.2885351413558813,"score_spread":0.2356294186040034,"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."}}