{"id":"W4416903361","doi":"10.3390/informatics12040133","title":"Fuzzy Ontology Embeddings and Visual Query Building for Ontology Exploration","year":2025,"lang":"en","type":"article","venue":"Informatics","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ontology; SPARQL; Fuzzy logic; Interface (matter); Semantics (computer science); Construct (python library); Query language; Flexibility (engineering); Ontology-based data integration","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001842463,0.0008102738,0.0004805988,0.001574741,0.0006646202,0.003146087,0.00143419,0.0010429,0.007034728],"category_scores_gemma":[0.007876685,0.000634285,0.001129718,0.000970846,0.001611758,0.006844151,0.004023456,0.001217592,0.001432315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007695367,"about_ca_system_score_gemma":0.0008672358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00253949,"about_ca_topic_score_gemma":0.003099538,"domain_scores_codex":[0.9985753,0.0004371416,0.0001322895,0.000237278,0.0005148452,0.0001031579],"domain_scores_gemma":[0.9975044,0.001341787,0.0001339409,0.000472134,0.0004093458,0.0001384818],"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":[0.0007867979,0.0003491115,0.001708986,0.0009527321,0.000106252,0.0008620666,0.005393152,0.0327553,0.06430158,0.4753161,0.02505615,0.3924118],"study_design_scores_gemma":[0.0001048472,0.0001457599,0.0007069185,0.000217053,0.00005686182,0.0008862661,0.001020149,0.5084264,0.06004062,0.3221491,0.1061078,0.000138184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008308194,0.000133797,0.9808804,0.0002629306,0.000030857,0.0001060548,0.000261927,0.006276011,0.003739819],"genre_scores_gemma":[0.1566432,0.0003129015,0.8375872,0.0002317186,0.00002635363,0.0002427573,0.001056506,0.0008946079,0.003004811],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007034728,"threshold_uncertainty_score":0.02353346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01775133116272598,"score_gpt":0.3147579712902761,"score_spread":0.2970066401275501,"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."}}