{"id":"W2971120804","doi":"10.14778/3352063.3352064","title":"GALO","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; IBM (Canada)","funders":"","keywords":"Computer science; SPARQL; Knowledge base; SQL; Query optimization; Process (computing); Query plan; Plan (archaeology); Information retrieval; Base (topology); RDF; Web query classification; Sargable; Database; Data mining; Web search query; World Wide Web; Search engine; Semantic Web; Programming language","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":[0.003044591,0.001482252,0.0009758264,0.002669,0.0009647626,0.005127639,0.003648122,0.00152594,0.1191751],"category_scores_gemma":[0.009577267,0.0008245737,0.001171535,0.001953715,0.0009106016,0.005481177,0.004886089,0.002633747,0.08732937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001738885,"about_ca_system_score_gemma":0.002243878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003790809,"about_ca_topic_score_gemma":0.003577903,"domain_scores_codex":[0.9966173,0.0004373313,0.0001777581,0.000897536,0.001509736,0.0003603724],"domain_scores_gemma":[0.9944537,0.001083124,0.0001905708,0.002219377,0.001582806,0.0004703345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001008517,0.0002805994,0.002508872,0.0006525862,0.00008520794,0.0002429332,0.0003575059,0.002515372,0.009650969,0.0384119,0.6089027,0.3353828],"study_design_scores_gemma":[0.0001791065,0.0001119097,0.001327543,0.0001187324,0.00003655697,0.0002629044,0.0001285506,0.0178202,0.006597551,0.02193326,0.9514161,0.00006765749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.01052587,0.001906054,0.2110727,0.004157265,0.001383906,0.001134677,0.0319982,0.376045,0.3617763],"genre_scores_gemma":[0.1566285,0.002621242,0.2908335,0.007931165,0.001153023,0.001276213,0.1750861,0.07154089,0.2929293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1191751,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00448911751621578,"score_gpt":0.1879691187956926,"score_spread":0.1834800012794768,"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."}}