{"id":"W2908623137","doi":"10.1002/aic.16532","title":"Long range pipeline leak detection and localization using discrete observer and support vector machine","year":2019,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Water Systems and Optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Discretization; Control theory (sociology); Linearization; Observer (physics); Mathematics; Partial differential equation; Nonlinear system; State vector; Applied mathematics; Computer science; Mathematical analysis; Physics; Artificial intelligence","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":[0.0004616017,0.000629577,0.0006335057,0.0002488977,0.0001997242,0.0005099798,0.0004986739,0.000722216,0.0005161348],"category_scores_gemma":[0.001047131,0.0002755659,0.0004204377,0.0002214837,0.0004546991,0.000719353,0.0005610526,0.0006731321,0.0001062945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003785688,"about_ca_system_score_gemma":0.0005176779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002745478,"about_ca_topic_score_gemma":0.001542145,"domain_scores_codex":[0.9997712,0.00006342948,0.00001579898,0.00006192275,0.0000645519,0.00002297963],"domain_scores_gemma":[0.9995232,0.0001979965,0.0001074316,0.00004519843,0.0001052442,0.00002093284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002023192,0.00007949567,0.00142785,0.0001305667,0.00005143299,0.0001070213,0.0001219274,0.8928246,0.02117087,0.003213848,0.000358182,0.0803119],"study_design_scores_gemma":[0.000003670809,0.0000242184,0.00006773169,0.000001345024,0.000002158517,0.000003555798,0.000002490506,0.9988079,0.0008944272,0.0001407923,0.00004956198,0.000002136446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04089103,0.00009468487,0.9579042,0.0000749748,0.00001904844,0.00001889327,0.000009398473,0.0003322288,0.0006556206],"genre_scores_gemma":[0.950352,0.00007121167,0.0486334,0.00001889015,0.00001012443,0.00005670849,0.00002972691,0.00001100861,0.0008169645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002745478,"threshold_uncertainty_score":0.005458951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009781508912874937,"score_gpt":0.2027032356732275,"score_spread":0.1929217267603526,"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."}}