{"id":"W2572321985","doi":"","title":"Building User Interest Profiles Using DBpedia in a Question Answering System.","year":2016,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Université Laval","funders":"","keywords":"Computer science; Categorical variable; Information retrieval; Term (time); Set (abstract data type); User modeling; Question answering; Linked data; World Wide Web; Data mining; Semantic Web; User interface; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.00571085,0.0001474288,0.0001930705,0.0001220239,0.0003313924,0.0003423028,0.001287078,0.0001075715,0.00000326997],"category_scores_gemma":[0.0001014683,0.00008223775,0.0001151469,0.0007061142,0.0001273423,0.0008235559,0.0008467585,0.0004516358,0.00001393294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006369564,"about_ca_system_score_gemma":0.000130153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029238,"about_ca_topic_score_gemma":0.00004437372,"domain_scores_codex":[0.997462,0.0006222212,0.0003190009,0.0004244267,0.0005364487,0.0006358438],"domain_scores_gemma":[0.9984837,0.0004120345,0.00006977651,0.0007373031,0.0002089987,0.00008825148],"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":[0.00002228668,0.00007717585,0.01095276,0.0005225251,0.00008385703,0.00004534304,0.00565242,0.00002913,0.1511457,0.7888322,0.01847484,0.02416172],"study_design_scores_gemma":[0.00475979,0.001098478,0.02471643,0.02375376,0.00003754455,0.0004930826,0.009862363,0.4888756,0.2858634,0.0726034,0.08442365,0.003512473],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3173525,0.0001679951,0.6760594,0.004448285,0.0006312215,0.000681451,0.000003321327,0.0003671488,0.0002887362],"genre_scores_gemma":[0.9772278,0.00006405588,0.02200392,0.00004691264,0.0004124109,0.0001175067,2.509496e-7,0.00001859672,0.0001085367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7162288,"threshold_uncertainty_score":0.3353558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1180784192410825,"score_gpt":0.3992222104433625,"score_spread":0.2811437912022801,"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."}}