{"id":"W4392167308","doi":"10.1111/obes.12602","title":"Multivariate Trend‐Cycle‐Seasonal Decompositions with Correlated Innovations*","year":2024,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Multivariate statistics; Econometrics; Seasonality; Seasonal adjustment; Exploit; Component (thermodynamics); Univariate; Multivariate analysis; Identification (biology); Consumption (sociology); Variable (mathematics); Economics; Statistics; Computer science; Mathematics","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":[0.002141866,0.0005915964,0.0006312143,0.001379569,0.0002297975,0.001141388,0.0004965258,0.0004083445,0.004673786],"category_scores_gemma":[0.005734163,0.0003996791,0.001121884,0.001932985,0.0005534616,0.001179159,0.0007354348,0.0009437946,0.0003765598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005326251,"about_ca_system_score_gemma":0.0009495622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005612514,"about_ca_topic_score_gemma":0.004667364,"domain_scores_codex":[0.9994026,0.0002381559,0.00003790715,0.000133375,0.0001011482,0.00008683472],"domain_scores_gemma":[0.9976591,0.001071523,0.0006021435,0.0003156937,0.0002380669,0.0001134706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001921915,0.000112987,0.02760522,0.000197084,0.0003067332,0.0003244882,0.000341444,0.3316894,0.006395739,0.5243664,0.004838946,0.1036294],"study_design_scores_gemma":[0.000007244741,0.00002448897,0.007107472,0.00001687236,0.00002641347,0.00004404585,0.00002715774,0.9184351,0.0003671348,0.07198356,0.001938325,0.00002216677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09423075,0.0003259405,0.90191,0.0003192889,0.00005072628,0.0000411601,0.0007783336,0.00028525,0.002058578],"genre_scores_gemma":[0.8924035,0.0008090147,0.09803302,0.0000667744,0.0001350709,0.0001308,0.001387907,0.0002209292,0.006813013],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005612514,"threshold_uncertainty_score":0.01563537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01329985838276815,"score_gpt":0.2159373649347197,"score_spread":0.2026375065519515,"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."}}