{"id":"W2171306790","doi":"10.48550/arxiv.1208.0293","title":"The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Interoperability; Ontology; Reusability; Ontology components; Standardization; Syntax; Extensibility; Semantics (computer science); Upper ontology; Web Ontology Language; Software engineering; Programming language; Ontology engineering; Modular design; Annotation; IDEF5; Information retrieval; World Wide Web; Semantic Web; Natural language processing; Artificial intelligence; Suggested Upper Merged Ontology; Software","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040062,0.0002777195,0.0003354575,0.00006699524,0.0003073438,0.0002240577,0.001298162,0.0002855034,0.000006431933],"category_scores_gemma":[0.0005134958,0.0002238958,0.0001244135,0.0002126569,0.0003835745,0.0003773969,0.002563134,0.0004803212,0.00002124257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001199363,"about_ca_system_score_gemma":0.0001046195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00210154,"about_ca_topic_score_gemma":0.001827139,"domain_scores_codex":[0.9981059,0.0002934719,0.0001841083,0.0008604922,0.00007162404,0.0004843464],"domain_scores_gemma":[0.996476,0.001332947,0.0001952661,0.001721928,0.0001139693,0.00015988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002337309,0.0003639874,0.2347074,0.0002242526,0.0004880101,0.006253602,0.001890008,0.001946465,0.0001172759,0.7366195,0.002280535,0.01487522],"study_design_scores_gemma":[0.001393701,0.000167593,0.8034142,0.0001596388,0.0004726069,0.000598657,0.001743711,0.1270386,0.0003689765,0.0558656,0.006781562,0.001995165],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8741826,0.00100164,0.1230974,0.0002969045,0.0007297901,0.0002489519,0.00004300036,0.0002429695,0.0001567382],"genre_scores_gemma":[0.9983686,0.0003048389,0.0008073263,0.00008403083,0.00005136259,9.002153e-7,0.00001684867,0.000007774539,0.0003583425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6807539,"threshold_uncertainty_score":0.9130206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09716730834734724,"score_gpt":0.2102151780649964,"score_spread":0.1130478697176492,"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."}}