{"id":"W2002032480","doi":"10.1109/wi.2004.111","title":"ONTOXPL - Intelligent Exploration of OWL Ontologies","year":2004,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Semantic reasoner; Computer science; OWL-S; Ontology; Web Ontology Language; Description logic; World Wide Web; Semantic Web; Information retrieval; Ontology language; Process ontology; Ontology Inference Layer; Complement (music); Semantic Web Stack; Artificial intelligence","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":[0.00176196,0.0009228662,0.0006072683,0.00145158,0.0006592567,0.002792961,0.001648971,0.0007497271,0.01569259],"category_scores_gemma":[0.0038031,0.0009825437,0.001267326,0.0009302102,0.0007046541,0.00540608,0.00495078,0.002027822,0.006278346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005874741,"about_ca_system_score_gemma":0.001027278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002109417,"about_ca_topic_score_gemma":0.00272552,"domain_scores_codex":[0.9988839,0.0002122541,0.00009715328,0.000176091,0.0005577434,0.00007288681],"domain_scores_gemma":[0.9991552,0.0003914102,0.00005487452,0.0002198557,0.0001047014,0.00007392319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006722643,0.0003727642,0.002212114,0.001209799,0.0001999894,0.002397838,0.001741747,0.008993215,0.03882761,0.1085703,0.2332378,0.6015646],"study_design_scores_gemma":[0.0003320434,0.0001063564,0.002303759,0.0002829747,0.00008252039,0.001623464,0.0005705281,0.203865,0.05100159,0.1404715,0.5992025,0.0001578113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007623994,0.0002166557,0.8255368,0.0005204239,0.00008728389,0.0004542533,0.005257429,0.1421718,0.01813137],"genre_scores_gemma":[0.07704644,0.0009201879,0.8392059,0.00087298,0.00008262091,0.0009053737,0.0335274,0.01622116,0.03121796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01569259,"threshold_uncertainty_score":0.05249697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07218751940172909,"score_gpt":0.2879070254471899,"score_spread":0.2157195060454608,"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."}}