{"id":"W2256821278","doi":"","title":"Seasonality adjusted quarterly GDP data","year":2004,"lang":"en","type":"article","venue":"Journal of Income & Wealth","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Seasonality; Multiplicative function; Seasonal adjustment; Standard deviation; Econometrics; Economics; Gross output; Real gross domestic product; Statistics; Mathematics; Agricultural economics; Geography; Macroeconomics; Production (economics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008791747,0.0003011065,0.0003348118,0.003378789,0.0002385827,0.0005874693,0.0004615084,0.0001627718,0.009146755],"category_scores_gemma":[0.005217244,0.0001520906,0.0003429245,0.007156968,0.0001170269,0.0003573857,0.0004767387,0.0005335189,0.003537182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006022818,"about_ca_system_score_gemma":0.001075083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02461921,"about_ca_topic_score_gemma":0.01655734,"domain_scores_codex":[0.9990107,0.0001367576,0.0001420362,0.0001475867,0.0004388345,0.000124055],"domain_scores_gemma":[0.9971023,0.0003503836,0.0005457969,0.0004552829,0.001461756,0.00008433784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009354153,0.0002839198,0.2457324,0.0008032086,0.0002711929,0.0004251817,0.001172094,0.02225477,0.006198673,0.01664323,0.3541511,0.3511289],"study_design_scores_gemma":[0.00004755471,0.0001796591,0.5324849,0.00008069548,0.00005873466,0.0003285712,0.0004228344,0.0067431,0.004464987,0.002690539,0.4524398,0.00005860485],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2215225,0.000713375,0.01750277,0.0005384352,0.0004956084,0.0004981543,0.7101252,0.001829269,0.04677469],"genre_scores_gemma":[0.2638257,0.001084763,0.01914859,0.0001685194,0.0001202943,0.0007064852,0.6882008,0.0005229978,0.0262218],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02461921,"threshold_uncertainty_score":0.04895186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06845247385307762,"score_gpt":0.2657716078160162,"score_spread":0.1973191339629386,"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."}}