{"id":"W2144324139","doi":"10.1109/imtc.2009.5168600","title":"UKF-based estimation fusion of Underbalanced Drilling Process using pressure sensors","year":2009,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Drilling; Robustness (evolution); Kalman filter; Annulus (botany); Underbalanced drilling; Process (computing); Computer science; Sensor fusion; Drilling fluid; Engineering; Mechanical engineering; Artificial intelligence; Materials science","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":[0.0009296351,0.0006507908,0.0009198472,0.0004479894,0.0002900353,0.0007200777,0.0005708103,0.000686025,0.0005461187],"category_scores_gemma":[0.002525176,0.000332898,0.0004047891,0.0005190302,0.0003434257,0.001326714,0.0005839922,0.0005659622,0.0002199718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004425155,"about_ca_system_score_gemma":0.0006860874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00482782,"about_ca_topic_score_gemma":0.002723126,"domain_scores_codex":[0.9994702,0.0001037545,0.00004418841,0.0001407751,0.0001689628,0.00007215641],"domain_scores_gemma":[0.9992355,0.0002570364,0.000138488,0.00007216687,0.0002701066,0.00002664443],"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":[0.0006888614,0.00009958626,0.002614887,0.0001972805,0.00007935962,0.000214979,0.0003255945,0.5661407,0.04888767,0.004539808,0.001069414,0.3751418],"study_design_scores_gemma":[0.00001117297,0.00004777091,0.0006506689,0.000004286346,0.000009417538,0.00002644435,0.000007964763,0.992395,0.005948067,0.000549893,0.0003388356,0.00001038532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05322266,0.0001804308,0.9453824,0.00007759922,0.00006214116,0.00001942285,0.00003972925,0.0004036669,0.0006118405],"genre_scores_gemma":[0.8826602,0.0001720306,0.1157799,0.00003731142,0.00003450466,0.00003977899,0.0001337774,0.00002262987,0.001119907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00482782,"threshold_uncertainty_score":0.009599447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008985209261850036,"score_gpt":0.2406911551210857,"score_spread":0.2317059458592357,"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."}}