{"id":"W4399543669","doi":"10.2139/ssrn.4859424","title":"On Robust Inference in Time Series Regression","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Inference; Series (stratigraphy); Regression; Time series; Econometrics; Computer science; Statistics; Mathematics; Artificial intelligence; Machine learning","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":[0.02699133,0.002992527,0.007244294,0.003204193,0.0009129373,0.003527645,0.005115913,0.00524709,0.004089594],"category_scores_gemma":[0.1200731,0.002548976,0.003767763,0.003824649,0.00477117,0.005264097,0.005024384,0.007403452,0.001164087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001876299,"about_ca_system_score_gemma":0.002459501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009457913,"about_ca_topic_score_gemma":0.004553684,"domain_scores_codex":[0.9868477,0.008355015,0.0008244111,0.001820541,0.001623026,0.0005292906],"domain_scores_gemma":[0.8526263,0.1355625,0.002704544,0.004929316,0.003552184,0.0006251539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003711881,0.0001376283,0.001171185,0.0005674013,0.001029579,0.0002541984,0.0001673581,0.7160109,0.001475216,0.1928526,0.003418199,0.08254458],"study_design_scores_gemma":[0.00002872217,0.00002891425,0.0001525338,0.00002610992,0.00004377141,0.00001507918,0.000006595921,0.9240085,0.0003163125,0.07475939,0.0005948448,0.00001912815],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001542142,0.0008520629,0.996375,0.0003538805,0.0001061711,0.00002069355,0.00004976572,0.0002078314,0.0004924223],"genre_scores_gemma":[0.3256106,0.006342514,0.6473281,0.001570471,0.0036848,0.0005966687,0.001869591,0.00117975,0.01181751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02699133,"threshold_uncertainty_score":0.1427454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004921669875344579,"score_gpt":0.2159960398002734,"score_spread":0.2110743699249288,"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."}}