{"id":"W4249243701","doi":"10.1145/568798.568801","title":"Design of knowledge-based systems with the ontology-domain-system approach","year":2002,"lang":"en","type":"article","venue":"Proceedings of the 14th international conference on Software engineering and knowledge engineering - SEKE '02","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Ontology; Unified Modeling Language; Software engineering; Domain engineering; Reuse; Process ontology; Domain knowledge; Ontology-based data integration; Feature-oriented domain analysis; Upper ontology; Domain analysis; Domain model; Suggested Upper Merged Ontology; Domain (mathematical analysis); Software development; Software; Programming language; Software construction; Engineering","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":[0.0004295043,0.0003164329,0.0003825064,0.0002472407,0.0001040159,0.0001593896,0.001495434,0.000114319,0.000002358227],"category_scores_gemma":[0.0002008789,0.0001981461,0.00007937531,0.0003623888,0.0001127285,0.0001835002,0.0002024309,0.0003008613,0.000003900825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008477649,"about_ca_system_score_gemma":0.00005457838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008111164,"about_ca_topic_score_gemma":4.550791e-7,"domain_scores_codex":[0.9986237,0.00001737185,0.0003496196,0.0003783807,0.0003319292,0.0002989957],"domain_scores_gemma":[0.9986455,0.0003034137,0.000198437,0.0002726812,0.0005080647,0.00007189321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008052537,0.0004595747,0.002406321,0.003101334,0.0006094003,0.000004860635,0.009384018,0.1589594,0.005892396,0.8150836,0.001206012,0.002812544],"study_design_scores_gemma":[0.0004536601,0.0001485635,0.000862813,0.0007739316,0.000024081,0.000052508,0.0002314516,0.9937598,0.00268888,0.00002199094,0.0007255764,0.0002567407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03043936,0.001065703,0.963764,0.0002490152,0.001147692,0.0004463074,0.000005897657,0.0004612645,0.002420815],"genre_scores_gemma":[0.9562394,0.00001557694,0.04334164,0.000006512701,0.00009552861,0.00007829117,6.167523e-7,0.00002471214,0.0001977325],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9258,"threshold_uncertainty_score":0.8080165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03187268500287949,"score_gpt":0.2116408756912467,"score_spread":0.1797681906883672,"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."}}