{"id":"W4400000452","doi":"10.1016/j.compchemeng.2024.108777","title":"Moving horizon estimation for pipeline leak detection, localization, and constrained size estimation","year":2024,"lang":"en","type":"article","venue":"Computers & Chemical Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Leak; Pipeline (software); Discretization; Estimator; Pipeline transport; Control theory (sociology); Observer (physics); Horizon; Mathematical optimization; Computer science; Engineering; Mathematics; Statistics; Artificial intelligence; Environmental engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009294154,0.0001760479,0.0001592584,0.00009485361,0.00003964376,0.000153605,0.00005419349,0.0001032023,0.000002440181],"category_scores_gemma":[0.00008768707,0.0001918853,0.000040349,0.0002022236,0.00001510969,0.0002487858,0.00001803796,0.00009453609,0.000002599015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000918684,"about_ca_system_score_gemma":0.000008014617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002669071,"about_ca_topic_score_gemma":0.000002234681,"domain_scores_codex":[0.999239,0.000003827263,0.0002819659,0.0002084036,0.00008652983,0.0001802593],"domain_scores_gemma":[0.999617,0.000159918,0.0000166061,0.00008932446,0.00004542426,0.00007167626],"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":[0.000002044461,0.000002630783,0.000001240064,0.0006309244,0.00001998937,0.00000108379,0.0001167222,0.9659452,0.01354756,0.0002596721,0.0005045814,0.0189683],"study_design_scores_gemma":[0.0002117912,0.00001686043,0.000004938253,0.0002354436,0.00002216661,0.00002274243,0.000004469623,0.974434,0.0239363,0.00009609766,0.0008160018,0.0001992023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005921195,0.0003568882,0.9914077,0.00003891304,0.0008862231,0.0002421872,0.000006180616,0.001110112,0.00003059367],"genre_scores_gemma":[0.9421569,0.000008273817,0.05743585,0.000008408492,0.0002277421,0.00003901702,0.00005398944,0.00005182332,0.00001801927],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9362357,"threshold_uncertainty_score":0.7824856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003902871979792074,"score_gpt":0.1817872447411305,"score_spread":0.1778843727613384,"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."}}