{"id":"W2788561287","doi":"10.48550/arxiv.1802.10233","title":"Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources","year":2018,"lang":"en","type":"article","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université TÉLUQ; University of Waterloo","funders":"UT-Battelle; Battelle; U.S. Department of Energy","keywords":"Computer science; Query optimization; Query language; Sargable; View; Extensibility; Architecture; Database; Relational database; Web search query; Programming language; Information retrieval; Database design","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":[0.0007081363,0.0001542281,0.0002201766,0.0002251698,0.0003361571,0.0005396781,0.001235533,0.00008621376,0.00003184021],"category_scores_gemma":[0.0001966331,0.0001340882,0.00005674584,0.0005018799,0.0005732906,0.003353344,0.0009207739,0.00004961537,0.000006515396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001901719,"about_ca_system_score_gemma":0.0001043106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008538501,"about_ca_topic_score_gemma":0.000006036188,"domain_scores_codex":[0.9982727,0.00001875487,0.0005668154,0.0003710304,0.0005228683,0.0002478065],"domain_scores_gemma":[0.998238,0.0001683537,0.0004185747,0.000781983,0.0003037892,0.00008933144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003217136,0.0007677476,0.000515421,0.0004400355,0.0002058336,0.000002027186,0.00005830079,0.0006464203,0.000379569,0.8368378,0.01786841,0.1419567],"study_design_scores_gemma":[0.004813234,0.001489661,0.01550248,0.0007447728,0.0003096921,0.00006721164,0.00003782169,0.2126814,0.01140631,0.03944369,0.7116541,0.001849678],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008813439,0.00008933342,0.9876299,0.0002534335,0.0003247335,0.0002334913,0.0002446124,0.00009052156,0.002320516],"genre_scores_gemma":[0.6254486,0.00001322022,0.3713575,0.0001903924,0.00006373542,0.00003051522,0.002797774,0.000005590044,0.00009258054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7973942,"threshold_uncertainty_score":0.5467958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0299497598105161,"score_gpt":0.279587591035751,"score_spread":0.2496378312252349,"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."}}