{"id":"W2797312554","doi":"10.1016/j.ssi.2018.04.004","title":"Phenomenological model of a solid electrolyte NOx and O2 sensor using temperature perturbation for on-board diagnostics","year":2018,"lang":"en","type":"article","venue":"Solid State Ionics","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Perturbation (astronomy); NOx; Oxygen sensor; Electrolyte; Temperature measurement; Automotive industry; Oxygen; Materials science; Automotive engineering; Chemistry; Thermodynamics; Physics; Electrode; Engineering; Physical chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002500835,0.0006083895,0.0006769765,0.0003614855,0.0006434599,0.001008013,0.001907093,0.002287042,0.00425799],"category_scores_gemma":[0.0006496626,0.0005891597,0.0008710196,0.0002960519,0.001148951,0.001554027,0.0007550267,0.0009202163,0.001005378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008711503,"about_ca_system_score_gemma":0.0008312656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007036664,"about_ca_topic_score_gemma":0.004099851,"domain_scores_codex":[0.9997792,0.00003379672,0.000008908357,0.00006702411,0.00007682374,0.00003425095],"domain_scores_gemma":[0.9997842,0.0000926174,0.00002225654,0.00002722118,0.00005795716,0.00001576779],"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":[0.000195596,0.0001204038,0.0008878479,0.0002397267,0.00006193226,0.0006526022,0.0002231894,0.9136199,0.05121332,0.02704451,0.0009485825,0.00479229],"study_design_scores_gemma":[0.00001627598,0.00003101277,0.0002726956,0.000006305634,0.0000122122,0.00005374945,0.00002154591,0.9939177,0.002499881,0.002616029,0.0005421229,0.00001041662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2377511,0.001362011,0.6627557,0.002117258,0.0004609504,0.0005584025,0.001538895,0.001268391,0.09218719],"genre_scores_gemma":[0.9748738,0.000406818,0.006925708,0.000181556,0.00004615846,0.0001841582,0.0001630403,0.00006134417,0.01715748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007036664,"threshold_uncertainty_score":0.01424438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02715082849263125,"score_gpt":0.28163368585741,"score_spread":0.2544828573647788,"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."}}