{"id":"W2752921427","doi":"10.14778/3137765.3137771","title":"Query-able Kafka","year":2017,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"SPARK (programming language); Computer science; Analytics; Downstream (manufacturing); Overhead (engineering); Pipeline (software); Upstream (networking); Big data; Order (exchange); Computer network; Data science; Data mining; Operating system; Engineering","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":[0.002072523,0.002769756,0.00139916,0.002422779,0.001579423,0.005194188,0.004857056,0.001744681,0.04645725],"category_scores_gemma":[0.01150141,0.001073704,0.002503205,0.002745207,0.00124228,0.008411454,0.006741965,0.002582067,0.03910277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001650122,"about_ca_system_score_gemma":0.002557724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009928129,"about_ca_topic_score_gemma":0.00974182,"domain_scores_codex":[0.996424,0.0004023922,0.0003598462,0.001168275,0.001139093,0.0005063632],"domain_scores_gemma":[0.9953832,0.0008177056,0.0001629167,0.002461566,0.0009083482,0.0002662706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003197288,0.0003669217,0.005542743,0.001249734,0.0003150736,0.0006450918,0.0009337052,0.0154702,0.02108207,0.05146389,0.6145762,0.2851571],"study_design_scores_gemma":[0.0004254203,0.0002183525,0.00299718,0.0001856266,0.0001325604,0.001055714,0.0009681588,0.3151059,0.03559323,0.1145766,0.5284517,0.0002895331],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.01565659,0.001143286,0.3243934,0.001624232,0.0005963613,0.0006528685,0.03278693,0.5802106,0.04293566],"genre_scores_gemma":[0.3616432,0.001211927,0.4087064,0.002773604,0.0004006816,0.00138543,0.1284945,0.04955611,0.04582817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04645725,"threshold_uncertainty_score":0.155415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167874254110153,"score_gpt":0.2509705654813036,"score_spread":0.2341831400702883,"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."}}