{"id":"W3149250894","doi":"","title":"Seasonal Adjustment of NIPA data","year":2018,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Seasonality; Seasonal adjustment; Residual; Quarter (Canadian coin); National Income and Product Accounts; Environmental science; Econometrics; Percentage point; Economics; Statistics; Geography; National accounts; Mathematics; Macroeconomics; Variable (mathematics)","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":[0.006206407,0.0004625945,0.0004937761,0.002697764,0.0006309667,0.00179501,0.001297752,0.0004424251,0.01098679],"category_scores_gemma":[0.03861125,0.0004375656,0.000701434,0.006392233,0.0002456211,0.001245961,0.00108809,0.002551918,0.007222646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001432875,"about_ca_system_score_gemma":0.00170622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03275763,"about_ca_topic_score_gemma":0.02511114,"domain_scores_codex":[0.9926677,0.001966842,0.0008509732,0.001250165,0.002724099,0.0005402228],"domain_scores_gemma":[0.9811033,0.003160746,0.002864686,0.003150897,0.009392017,0.00032832],"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":[0.0004298047,0.0002355468,0.119427,0.0005608121,0.0004088679,0.0001663876,0.0007295319,0.008397874,0.001725082,0.01182748,0.6652907,0.1908009],"study_design_scores_gemma":[0.00007555036,0.00009498831,0.2790663,0.0001697453,0.0001143211,0.0001689694,0.0006490292,0.01963693,0.003398648,0.00625856,0.6902651,0.0001019632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.1556225,0.001807672,0.08057601,0.009684922,0.006281389,0.002290189,0.6108657,0.006259921,0.1266118],"genre_scores_gemma":[0.3157511,0.001133972,0.04317355,0.002762164,0.001163038,0.002671364,0.5906947,0.002657388,0.03999261],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03275763,"threshold_uncertainty_score":0.06513393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09674482089444335,"score_gpt":0.3174758779266355,"score_spread":0.2207310570321921,"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."}}