{"id":"W3047647804","doi":"10.1061/9780784483213.024","title":"Finding Big Leaks with Big Data: Case Studies from an Internet-of-Things Leak Detection Platform","year":2020,"lang":"en","type":"article","venue":"Pipelines 2020","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics","funders":"","keywords":"Big data; Leak; Internet of Things; Computer science; Leak detection; Computer security; Embedded system; Data mining; 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":[0.003908627,0.0006914742,0.0004831996,0.001479228,0.001985615,0.00154561,0.001524789,0.002562116,0.000608302],"category_scores_gemma":[0.01302645,0.0003694493,0.0005235141,0.002756909,0.002548434,0.003683223,0.002430535,0.001801156,0.0002893663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008185371,"about_ca_system_score_gemma":0.0009952665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004857311,"about_ca_topic_score_gemma":0.01118511,"domain_scores_codex":[0.9955143,0.001617744,0.0002712302,0.0003333647,0.001913694,0.0003496065],"domain_scores_gemma":[0.9804311,0.01272737,0.001921194,0.00165331,0.002332096,0.0009348675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001956806,0.003955876,0.3325212,0.004610745,0.0006659108,0.09324926,0.09110111,0.09011103,0.04031826,0.01842912,0.03748601,0.2855946],"study_design_scores_gemma":[0.0003332865,0.005941262,0.2908545,0.001222487,0.0003933419,0.03436678,0.2376157,0.2026311,0.06490786,0.02950752,0.131563,0.0006631469],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609314,0.0003991002,0.02966065,0.002568836,0.00008101705,0.0004861846,0.0007267895,0.0003631174,0.004782952],"genre_scores_gemma":[0.9651318,0.0006339852,0.03044821,0.0004516726,0.00005636573,0.0002154766,0.0007477301,0.0001084073,0.00220638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004857311,"threshold_uncertainty_score":0.02067107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1429447404586784,"score_gpt":0.3235493404215648,"score_spread":0.1806045999628864,"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."}}