{"id":"W1601845256","doi":"10.3233/978-1-60750-535-8-147","title":"On Building an Index Advisor for Semantic Web Queries","year":2010,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Index (typography); Computer science; Information retrieval; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002221402,0.000274518,0.0003499504,0.0003373182,0.000266136,0.0002016512,0.0007999095,0.0003478729,0.00001167918],"category_scores_gemma":[0.00004301443,0.0002724011,0.00007057011,0.00009938195,0.0002885046,0.0002140763,0.0001101071,0.000396815,0.0000210466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003227897,"about_ca_system_score_gemma":0.00009436582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001797651,"about_ca_topic_score_gemma":0.0002523413,"domain_scores_codex":[0.9984109,0.00001106374,0.0004326496,0.0006992693,0.0001621335,0.0002839942],"domain_scores_gemma":[0.998815,0.0001640137,0.0001657083,0.0006821773,0.00008178928,0.00009133112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001043946,0.0000310523,0.00001664613,0.0000200512,0.000009056434,0.000001194282,0.0001159368,0.00004274519,0.0001177429,0.7824855,0.0003612837,0.2167884],"study_design_scores_gemma":[0.00002250555,0.0001009254,0.00001316583,0.00005751051,0.00001343702,0.000002693556,0.0001151884,0.02638295,0.001371699,0.8967586,0.07484648,0.000314808],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001497827,0.0003280281,0.9880344,0.0006637123,0.00061203,0.0008724048,0.00002105689,0.0001255735,0.009193062],"genre_scores_gemma":[0.3123354,0.001879287,0.650982,0.001365797,0.001615335,0.002267077,0.0001009656,0.000175132,0.02927895],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3370523,"threshold_uncertainty_score":0.9999728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03789830351253307,"score_gpt":0.2927903802435642,"score_spread":0.2548920767310311,"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."}}