{"id":"W4417249410","doi":"10.1109/mecon67253.2025.11276981","title":"Investigating the Impact of Correlated Variables in Building a Virtual Sensor Model","year":2025,"lang":"","type":"article","venue":"","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Sensor fusion; Correlation; Virtual machine; Data acquisition; Soft sensor; Support vector machine; Physical system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001732154,0.0002875465,0.0003665948,0.000113924,0.0003230793,0.00006798362,0.0004392593,0.0002024268,0.0002266386],"category_scores_gemma":[0.0007681852,0.0002006163,0.0001747689,0.001281115,0.0006014463,0.0002322525,0.0005032977,0.0005850527,0.00001325808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005367624,"about_ca_system_score_gemma":0.0001702963,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009105072,"about_ca_topic_score_gemma":0.00002294436,"domain_scores_codex":[0.9975777,0.0002294701,0.0008721668,0.0004402288,0.0003240414,0.0005563453],"domain_scores_gemma":[0.9985151,0.0006924131,0.0002793357,0.0003911531,0.00002000336,0.0001019549],"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":[0.00001441571,0.00007718731,0.1396427,0.00001970204,0.00004541203,8.473601e-7,0.002608971,0.8133491,0.03424572,0.002009945,0.00007690793,0.007909042],"study_design_scores_gemma":[0.0003838104,0.00009167036,0.04672888,0.0005543472,0.00003033467,0.000002032561,0.001923059,0.94318,0.003736999,0.003177823,0.000002045242,0.0001889957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637254,0.00006857913,0.02784977,0.0002099056,0.0002021922,0.0002668517,0.00001381908,0.00003095029,0.007632504],"genre_scores_gemma":[0.9909989,0.00001693985,0.006864632,0.00005175403,0.00002792776,0.000005944669,7.947402e-7,0.00001460174,0.002018464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1298309,"threshold_uncertainty_score":0.9974934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03062088115852203,"score_gpt":0.3040579030024011,"score_spread":0.2734370218438791,"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."}}