{"id":"W4291713239","doi":"10.1145/3183713.3190662","title":"Apache Calcite","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":138,"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; Extensibility; Architecture; Relational database; Sargable; View; Calcite; Database; Programming language; Web search query; 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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0003494487,0.0002095255,0.0001954282,0.0001164034,0.00009511234,0.0003628195,0.002243011,0.0001496603,0.00004034898],"category_scores_gemma":[0.00001533168,0.0001673469,0.000142175,0.000149007,0.00004751012,0.000006366846,0.00846795,0.0002239244,0.0004699294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000468011,"about_ca_system_score_gemma":0.00004467232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008820045,"about_ca_topic_score_gemma":0.000003653817,"domain_scores_codex":[0.9984431,0.00005626069,0.0002073234,0.000697041,0.0003071647,0.000289083],"domain_scores_gemma":[0.9981676,0.00003393619,0.0001017649,0.001541366,0.00006442983,0.0000908455],"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":[0.000005182946,0.0003189587,0.0006540887,0.0004132259,0.0004198953,0.0001251711,0.003338333,0.02815143,0.00002654726,0.1772916,0.4323602,0.3568954],"study_design_scores_gemma":[0.0001268712,0.00004260215,0.0007777724,0.0001015666,0.00001324446,0.000006359687,0.00001229419,0.8746229,0.0001652629,0.02061446,0.103034,0.0004826084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03020055,0.0001124966,0.7917041,0.002548902,0.002022707,0.0001899358,6.665299e-7,0.0009612861,0.1722594],"genre_scores_gemma":[0.7521799,0.000007285921,0.1965553,0.00270134,0.001763452,0.00002899746,0.00000489092,0.00003349987,0.04672539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8464715,"threshold_uncertainty_score":0.9995514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522563115720203,"score_gpt":0.258807168560342,"score_spread":0.2335815374031399,"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."}}