{"id":"W2031959081","doi":"10.1109/vlhcc.2009.5295284","title":"Using a degree of interest model to facilitate ontology navigation","year":2009,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Protégé; Ontology; Plug-in; Task (project management); Human–computer interaction; Process ontology; Ontology-based data integration; Upper ontology; Information retrieval; Data science; Software engineering; Domain knowledge; Semantic Web; 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":[0.005267447,0.0006287645,0.0006032654,0.001906475,0.0009386452,0.005011799,0.001933685,0.001731421,0.003340557],"category_scores_gemma":[0.02098496,0.0007272984,0.001256509,0.001904598,0.001061639,0.01067352,0.003315499,0.002799148,0.001719066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545604,"about_ca_system_score_gemma":0.001440338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00493832,"about_ca_topic_score_gemma":0.01342303,"domain_scores_codex":[0.9966624,0.0012635,0.0003191443,0.0005293366,0.001062016,0.0001636415],"domain_scores_gemma":[0.9914725,0.004894016,0.0005508841,0.001898782,0.0009131994,0.0002706261],"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":[0.0005599681,0.0004554433,0.006687471,0.0004956559,0.0001604391,0.0009896839,0.003573095,0.08463921,0.01733186,0.5717551,0.01804402,0.2953081],"study_design_scores_gemma":[0.00007767168,0.0001310473,0.001036388,0.0001391319,0.000109576,0.0008129663,0.0003405481,0.6515176,0.01313456,0.1709615,0.1616376,0.0001014786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005750186,0.0001069845,0.9872425,0.0005595189,0.00003099213,0.0001134233,0.0001639918,0.002376959,0.003655506],"genre_scores_gemma":[0.2072315,0.0004077904,0.7857266,0.0003081767,0.00004713403,0.0002090073,0.000856475,0.0005441995,0.004669152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005267447,"threshold_uncertainty_score":0.02785724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4156447705046137,"score_gpt":0.3526707339119261,"score_spread":0.06297403659268763,"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."}}