{"id":"W3086973390","doi":"10.14778/3407790.3407858","title":"ATHENA++","year":2020,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Benchmark (surveying); SQL; Query language; Set (abstract data type); Ontology; Nesting (process); Information retrieval; Programming language; Database","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":[0.00009559963,0.00007745857,0.000113887,0.00001583086,0.00005175779,0.0000487947,0.001280146,0.00002073398,0.000006166864],"category_scores_gemma":[0.00009978203,0.00004649694,0.00007338549,0.000219767,0.00003973246,0.0001695663,0.0005687607,0.00006709908,0.00001829086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001267764,"about_ca_system_score_gemma":0.00001411188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009286717,"about_ca_topic_score_gemma":2.392743e-7,"domain_scores_codex":[0.9992865,0.000002391116,0.0001414853,0.0001863084,0.000233647,0.0001496067],"domain_scores_gemma":[0.9996657,0.00001835307,0.0001011711,0.0001044592,0.00006230857,0.00004801114],"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":[0.00002000175,0.0001031015,0.01421938,0.000163837,0.00006544538,0.000001574507,0.008324417,0.00001426423,0.1138543,0.8201597,0.02350556,0.01956832],"study_design_scores_gemma":[0.0007839324,0.0002774203,0.0119349,0.00007565153,0.00002862291,0.00001863778,0.0006988395,0.007215099,0.9077232,0.03988873,0.03104684,0.0003080759],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7002492,0.0009199088,0.01461828,0.1754993,0.001157763,0.001136776,0.000003081986,0.0008205306,0.1055951],"genre_scores_gemma":[0.9901609,0.00001478686,0.008392509,0.001280635,0.00005091617,0.000008805714,2.931521e-8,0.000003467676,0.00008788554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7938689,"threshold_uncertainty_score":0.2378851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196695787347267,"score_gpt":0.2013119211773401,"score_spread":0.1793449633038674,"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."}}