{"id":"W2963494503","doi":"10.1609/aaai.v33i01.33013526","title":"Improved Knowledge Graph Embedding Using Background Taxonomic Information","year":2019,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Embedding; Knowledge graph; Computer science; Theoretical computer science; Graph; Mathematics; Artificial intelligence","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":[0.001220707,0.001006579,0.001001628,0.001725963,0.0006084003,0.00185833,0.001573361,0.001289058,0.003400674],"category_scores_gemma":[0.008158849,0.0005517201,0.001571419,0.002256518,0.0007632439,0.007797005,0.00268013,0.002345285,0.001241773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008771682,"about_ca_system_score_gemma":0.001096231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004811972,"about_ca_topic_score_gemma":0.007665599,"domain_scores_codex":[0.9987757,0.0003311099,0.00007499018,0.0004463762,0.0002783225,0.00009349614],"domain_scores_gemma":[0.9954514,0.001927937,0.0003080635,0.001752842,0.0004068537,0.0001528821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003027234,0.000489266,0.003082246,0.0005961262,0.0002249466,0.0004496987,0.0009802454,0.2902101,0.01513492,0.1156062,0.02125841,0.5516651],"study_design_scores_gemma":[0.00001447313,0.0000289556,0.0003004952,0.00002767071,0.00004253483,0.00009954139,0.00009201456,0.9183522,0.002222016,0.0749045,0.003899832,0.0000156738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03056712,0.0003644997,0.9635743,0.0005035035,0.00004046696,0.00007053788,0.0008966487,0.002181559,0.00180137],"genre_scores_gemma":[0.4337909,0.0007284955,0.5492944,0.0002921506,0.0001138437,0.0001747292,0.007373908,0.0006751884,0.007556533],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004811972,"threshold_uncertainty_score":0.01137644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03363265289143851,"score_gpt":0.2717997519343149,"score_spread":0.2381670990428764,"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."}}