{"id":"W2043554371","doi":"10.1007/s10009-006-0002-1","title":"MDA-based Automatic OWL Ontology Development","year":2006,"lang":"en","type":"article","venue":"International Journal on Software Tools for Technology Transfer","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; OWL-S; Metamodeling; Process ontology; Ontology; Ontology Inference Layer; Programming language; Ontology-based data integration; Web Ontology Language; Upper ontology; Suggested Upper Merged Ontology; Software engineering; Semantic Web; Information retrieval; Semantic Web Stack","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":[0.001805838,0.00046959,0.0004123661,0.001456883,0.0007038115,0.001462429,0.0009178463,0.0005511018,0.004109594],"category_scores_gemma":[0.0053693,0.0007348568,0.0008884438,0.0006853492,0.0003759095,0.002074302,0.001476923,0.001217163,0.001511673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005300587,"about_ca_system_score_gemma":0.001656107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00381577,"about_ca_topic_score_gemma":0.005791586,"domain_scores_codex":[0.9988747,0.0003202375,0.000102628,0.0001316755,0.0004800651,0.00009059735],"domain_scores_gemma":[0.9977041,0.0007875596,0.0001310666,0.000695308,0.0006236976,0.00005832301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002207085,0.0005793751,0.004981014,0.0004061452,0.0002016619,0.0006911676,0.001121831,0.02621171,0.05946535,0.05015914,0.02451864,0.8314433],"study_design_scores_gemma":[0.00008905292,0.00009378696,0.002572386,0.0001614231,0.0001906904,0.0006851403,0.0004735932,0.7888246,0.09760129,0.03742456,0.07181332,0.00007008306],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01435625,0.00005264976,0.9657437,0.0001142447,0.00004907966,0.0001614163,0.0002444514,0.01570627,0.003572033],"genre_scores_gemma":[0.1463622,0.0001167762,0.8470839,0.00009757325,0.00001032804,0.0001833157,0.001781509,0.001844145,0.002520179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004109594,"threshold_uncertainty_score":0.01374793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995519643688351,"score_gpt":0.2646745578526939,"score_spread":0.2447193614158104,"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."}}