{"id":"W7019045528","doi":"","title":"Event Stream Processing with Beep Beep 3 : Log crunching and analysis made easy","year":2018,"lang":"en","type":"book","venue":"BiblioBoard Library Catalog (Open Research Library)","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Event (particle physics); Process (computing); Transaction processing; Troubleshooting; Filter (signal processing)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001277078,0.001866758,0.0009003656,0.001515838,0.0005489876,0.003715386,0.002471189,0.001369942,0.069794],"category_scores_gemma":[0.005730872,0.001250203,0.001109396,0.001386808,0.0006994248,0.003348284,0.002620948,0.002746265,0.02678321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005739139,"about_ca_system_score_gemma":0.0007315874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002572285,"about_ca_topic_score_gemma":0.00320978,"domain_scores_codex":[0.9985799,0.0001464119,0.00009680772,0.0002322299,0.0008390695,0.0001056268],"domain_scores_gemma":[0.9978316,0.0008344083,0.00009610228,0.0004691239,0.0006275824,0.0001411533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001236553,0.0001698274,0.001202046,0.0009622131,0.0001431647,0.0009871883,0.0008229383,0.007530663,0.03227873,0.0235331,0.4006157,0.5305178],"study_design_scores_gemma":[0.0003298009,0.0002227371,0.002455571,0.0005967468,0.0001041307,0.001335591,0.0003014292,0.1362765,0.07532814,0.05717884,0.7255393,0.0003312218],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002820964,0.000782185,0.7634245,0.0008803782,0.0006380295,0.0003815287,0.004284376,0.198194,0.02859402],"genre_scores_gemma":[0.05558754,0.00167595,0.8006445,0.002499396,0.0003190405,0.0009857782,0.01089609,0.04102946,0.08636227],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.069794,"threshold_uncertainty_score":0.2334842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03716945310582175,"score_gpt":0.309489270395327,"score_spread":0.2723198172895052,"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."}}