{"id":"W2991568540","doi":"10.1016/j.procs.2019.11.079","title":"COMPETENCY QUESTIONS FOR BIOMEDICAL ONTOLOGY REUSE","year":2019,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Reuse; Ontology; Interoperability; Domain (mathematical analysis); Scope (computer science); Process (computing); Ontology engineering; Upper ontology; Process ontology; Open Biomedical Ontologies; Software engineering; Data science; Semantics (computer science); Semantic interoperability; Knowledge management; Domain knowledge; World Wide Web; Suggested Upper Merged Ontology; Programming language","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":[0.03413162,0.00101661,0.0008905394,0.005554719,0.003347492,0.004939138,0.002238337,0.004363256,0.002928735],"category_scores_gemma":[0.1360487,0.0007404446,0.002406392,0.002491967,0.012272,0.01883399,0.01050898,0.004603634,0.0006402102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004244849,"about_ca_system_score_gemma":0.006167565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009754376,"about_ca_topic_score_gemma":0.00400629,"domain_scores_codex":[0.9592085,0.02515478,0.00421085,0.003788903,0.006324885,0.00131219],"domain_scores_gemma":[0.8889947,0.07468751,0.006196424,0.0121338,0.01567402,0.002313558],"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":[0.00005227629,0.0001351606,0.003654766,0.0003234086,0.00006875602,0.0005666413,0.0074602,0.005956188,0.001348013,0.8985214,0.003004014,0.07890918],"study_design_scores_gemma":[0.0000288767,0.0000419153,0.001231135,0.0003493257,0.00004537587,0.0005055618,0.003264249,0.02580732,0.002158447,0.9342074,0.03228137,0.00007901942],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03754349,0.000924271,0.9241932,0.01626081,0.0001703449,0.0005322301,0.0002587422,0.0002836612,0.01983322],"genre_scores_gemma":[0.4673743,0.000573032,0.5244488,0.002076337,0.0002409663,0.0006883604,0.0007047147,0.0001577587,0.003735791],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03413162,"threshold_uncertainty_score":0.1805074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072013064663748,"score_gpt":0.2784180533142503,"score_spread":0.2676979226676128,"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."}}