{"id":"W4410155222","doi":"10.2139/ssrn.5239347","title":"ENHANCING SPARQL QUERY REWRITING FOR COMPLEX ONTOLOGY ALIGNMENTS","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"SPARQL; Computer science; Rewriting; Information retrieval; Ontology; Named graph; RDF; Programming language; Semantic Web","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":[0.004546247,0.001091318,0.001480141,0.001431444,0.001028324,0.003830774,0.002474367,0.001460371,0.008989073],"category_scores_gemma":[0.0208141,0.0008785404,0.001772641,0.002463906,0.001093816,0.005077425,0.00408462,0.002371383,0.004388928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018272,"about_ca_system_score_gemma":0.002011655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005734394,"about_ca_topic_score_gemma":0.009021418,"domain_scores_codex":[0.9898828,0.002552824,0.001031632,0.001309371,0.004534659,0.0006887809],"domain_scores_gemma":[0.9844319,0.006971878,0.0006166386,0.004390029,0.003342838,0.0002467325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001119619,0.00110388,0.00817625,0.001819503,0.0006162426,0.002725914,0.003246719,0.06942233,0.1163286,0.1094111,0.0608777,0.6251522],"study_design_scores_gemma":[0.0002209237,0.0002541175,0.001900188,0.0001581123,0.0004391563,0.001675649,0.001540774,0.6558011,0.1164516,0.1315614,0.08980203,0.0001949141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05109353,0.0005481893,0.9120011,0.0007893786,0.0003430962,0.0004881512,0.00147559,0.02357686,0.009684019],"genre_scores_gemma":[0.2979937,0.0004973714,0.676252,0.0009146517,0.0002034629,0.0001888252,0.005975454,0.008030491,0.009943981],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008989073,"threshold_uncertainty_score":0.03007144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01789470928632094,"score_gpt":0.2900202557058834,"score_spread":0.2721255464195625,"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."}}