{"id":"W91053303","doi":"10.5006/c2001-01283","title":"Applications of Electrochemical Noise: Real Time Plant and Field Challenges","year":2001,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Chevron (Canada)","funders":"","keywords":"Electrochemical noise; Noise (video); Electrochemistry; Field (mathematics); Materials science; Electrical engineering; Electronic engineering; Computer science; Acoustics; Environmental science; Electrode; Engineering; 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":[0.001207969,0.0003037225,0.000378298,0.0003803788,0.0003230562,0.0009743599,0.0009029684,0.001990787,0.00239075],"category_scores_gemma":[0.002877757,0.0001676871,0.0001618789,0.0004850316,0.0006996221,0.001113133,0.000556561,0.0008582482,0.0007184949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004144763,"about_ca_system_score_gemma":0.0003040379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007237683,"about_ca_topic_score_gemma":0.0006752361,"domain_scores_codex":[0.9990342,0.0002384184,0.00003658427,0.0001283115,0.0005168448,0.00004565578],"domain_scores_gemma":[0.996283,0.002085306,0.0002229331,0.0002520955,0.001012528,0.0001442412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005711248,0.0002801013,0.007144778,0.001022198,0.00005571509,0.001811181,0.0005083028,0.07871016,0.2450411,0.01430145,0.009132069,0.6414218],"study_design_scores_gemma":[0.0001548681,0.002527876,0.01208897,0.0002378377,0.000095344,0.01542698,0.00151501,0.496152,0.3341918,0.04108943,0.09626994,0.0002500154],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2931207,0.009387695,0.6710188,0.007859343,0.000502156,0.000100261,0.0001430792,0.001383451,0.01648441],"genre_scores_gemma":[0.9170483,0.004073174,0.06929807,0.0005909809,0.000317797,0.00003862985,0.0001055454,0.00006898281,0.008458474],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.00239075,"threshold_uncertainty_score":0.007997811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185882079519179,"score_gpt":0.2550944183840944,"score_spread":0.2432355975889026,"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."}}