{"id":"W2112517672","doi":"10.1109/cnsm.2010.5691320","title":"An extensible framework for repair-driven monitoring","year":2010,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Context (archaeology); Autonomic computing; Event (particle physics); Probabilistic logic; Focus (optics); Reliability engineering; Imperfect; Dimension (graph theory); Risk analysis (engineering); Controller (irrigation); Artificial intelligence; 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":[0.00515532,0.001376063,0.00108093,0.001337953,0.0007601471,0.003093628,0.005697351,0.002198901,0.004715786],"category_scores_gemma":[0.005347855,0.001187401,0.001925735,0.0008518062,0.00162867,0.003620694,0.004147216,0.003963684,0.002083636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008991606,"about_ca_system_score_gemma":0.001252079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002552545,"about_ca_topic_score_gemma":0.00256285,"domain_scores_codex":[0.997696,0.0004906955,0.0003036236,0.0004534118,0.0008744127,0.0001818342],"domain_scores_gemma":[0.9977031,0.0006563457,0.0002462676,0.0008504156,0.000338355,0.0002054157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000231091,0.0002159438,0.0019219,0.0004288145,0.0002112611,0.001118632,0.000706379,0.2436535,0.01710805,0.5126371,0.008174654,0.2135926],"study_design_scores_gemma":[0.0000721223,0.0001340308,0.0003134725,0.0001357639,0.0001075467,0.000655622,0.00005119375,0.7366069,0.006024051,0.16787,0.08793169,0.00009768621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000695243,0.0001541877,0.9948873,0.0000987789,0.00005239093,0.000083846,0.00004201712,0.00283753,0.001148765],"genre_scores_gemma":[0.0766447,0.0006506865,0.9160627,0.0002207059,0.0001757536,0.0005290235,0.0002934874,0.0006256057,0.00479726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005697351,"threshold_uncertainty_score":0.0272643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01860053601704522,"score_gpt":0.3093990483591438,"score_spread":0.2907985123420986,"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."}}