{"id":"W2081800170","doi":"10.1002/jae.1213","title":"An identification‐robust test for time‐varying parameters in the dynamics of energy prices","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada; Carleton University; McGill University; Université Laval","funders":"Université de Montréal; Université Laval","keywords":"Econometrics; Residual; Sample (material); Identification (biology); Coal; Oil price; Residual oil; Statistics; Economics; Computer science; Mathematics; Petroleum engineering; Engineering","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":[0.01603326,0.0007417992,0.001681696,0.001459055,0.0004620789,0.001645135,0.002043665,0.001685181,0.005786969],"category_scores_gemma":[0.07927639,0.000665221,0.001509622,0.001148644,0.001107675,0.002368777,0.001966224,0.002301288,0.0007368047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006195132,"about_ca_system_score_gemma":0.001925892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00319905,"about_ca_topic_score_gemma":0.002071054,"domain_scores_codex":[0.9897972,0.005231442,0.0008637977,0.001973793,0.001599894,0.0005338051],"domain_scores_gemma":[0.8491952,0.1226757,0.01530427,0.007588372,0.003856872,0.001379681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001794287,0.001560976,0.388027,0.0004445548,0.006210671,0.001080715,0.0006750157,0.3377208,0.01508259,0.04293606,0.006097802,0.1983696],"study_design_scores_gemma":[0.0003551916,0.001490556,0.09949277,0.00004826887,0.000524807,0.000310963,0.000353823,0.8634171,0.008480747,0.02272198,0.002639078,0.0001648282],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6914514,0.0002843889,0.297251,0.00120173,0.0001210771,0.0002210577,0.001762773,0.001224034,0.00648253],"genre_scores_gemma":[0.9844393,0.00004088058,0.01367528,0.00008220215,0.00002975484,0.0000610588,0.0009752018,0.00004418584,0.0006520424],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01603326,"threshold_uncertainty_score":0.08479303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543894267400276,"score_gpt":0.2218985043053188,"score_spread":0.1964595616313161,"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."}}