{"id":"W4404510353","doi":"10.2316/j.2024.206-0922","title":"A NOVEL INTELLIGENT FAULT OBSERVER TO DIAGNOSE ACTUATOR FAULT AND SENSOR NOISE BASED ON PROBABILITY DISTRIBUTIONS, 1-12.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Observer (physics); Actuator; Fault (geology); Noise (video); Computer science; Control theory (sociology); Artificial intelligence; Physics; Control (management); Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002721423,0.0001063182,0.000127415,0.0001832595,0.00003916009,0.0002656345,0.00007980264,0.00005798649,0.0000129768],"category_scores_gemma":[0.0002249005,0.00009248489,0.00006100975,0.00007522955,0.00001666411,0.0001684873,0.00001307223,0.0001409056,0.000006456444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002083631,"about_ca_system_score_gemma":0.00003645863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001474542,"about_ca_topic_score_gemma":0.00001914316,"domain_scores_codex":[0.9991106,0.0000242298,0.0003533083,0.0001040732,0.0003154293,0.0000923951],"domain_scores_gemma":[0.9994166,0.0001493911,0.00005573354,0.00006229396,0.0002025436,0.0001134242],"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":[0.00008871294,0.0001641663,0.0005668194,0.0001616662,0.0002397662,0.00004562475,0.0005904025,0.9012527,0.01299523,0.004219043,0.000961378,0.07871452],"study_design_scores_gemma":[0.0003948688,0.00009343365,0.00447689,0.0003785515,0.00002461219,0.00006104685,0.00005422843,0.9832703,0.001049986,0.0001913629,0.009889278,0.0001154593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4279532,0.0002835908,0.5642997,0.004483738,0.002373095,0.0002795535,0.00009348526,0.0001343321,0.00009931493],"genre_scores_gemma":[0.9955907,0.00007463415,0.003971281,0.00008248269,0.0002202689,0.00000806785,0.000009330671,0.00001184123,0.00003139747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5676375,"threshold_uncertainty_score":0.3771425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519004808670572,"score_gpt":0.2541019303311755,"score_spread":0.2389118822444698,"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."}}