{"id":"W3138240437","doi":"10.14778/3407790.3407806","title":"Knowledge translation","year":2020,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Heuristics; SPARQL; Set (abstract data type); Ranking (information retrieval); Information retrieval; Translation (biology); Rank (graph theory); Semantic mapping; Natural language processing; Artificial intelligence; Data mining; Semantic Web; RDF; Programming language; Mathematics","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":[0.00009419574,0.00006806241,0.00009712015,0.00001871257,0.00004745171,0.00003876513,0.0007918405,0.00002194876,0.000004147763],"category_scores_gemma":[0.000053866,0.00004351744,0.00006411762,0.0002446472,0.00002938554,0.0001909648,0.0001777003,0.00005719724,0.00001403119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001119264,"about_ca_system_score_gemma":0.00001504313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004520957,"about_ca_topic_score_gemma":6.374464e-7,"domain_scores_codex":[0.999432,0.000003095612,0.0001378497,0.0001606264,0.0001510557,0.000115413],"domain_scores_gemma":[0.9997293,0.00002649904,0.0000745946,0.00007108568,0.00006170494,0.00003686962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003632313,0.0002137757,0.008261106,0.0003951079,0.00008272687,7.484193e-7,0.03454797,0.00002583736,0.2274045,0.5295998,0.01491118,0.1845209],"study_design_scores_gemma":[0.001042213,0.0002576227,0.008925303,0.00008837228,0.00003659886,0.000009497584,0.0007331523,0.02721376,0.9068916,0.02045552,0.03404786,0.0002985286],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4910165,0.004431129,0.05880645,0.1656281,0.001837136,0.002061996,0.000004484601,0.001152321,0.2750619],"genre_scores_gemma":[0.9910116,0.00001614763,0.00856821,0.0002994859,0.00004691046,0.000008393969,5.569713e-8,0.000002964166,0.00004624846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.679487,"threshold_uncertainty_score":0.177459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08498789382318941,"score_gpt":0.2627009697317941,"score_spread":0.1777130759086047,"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."}}