{"id":"W2267200606","doi":"10.6338/jda.201110_6(5).0008","title":"X-12-ARIMA对中国季度GDP的探索","year":2011,"lang":"zh","type":"article","venue":"Journal of Data Analysis","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; China; Real gross domestic product; Quarter (Canadian coin); Index (typography); Economics; Seasonal adjustment; Econometrics; GDP deflator; Gross domestic product; Accounting; Statistics; Geography; Time series; Mathematics; Macroeconomics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008838317,0.0001932715,0.0005488718,0.0007047066,0.0001519254,0.0001551035,0.004566672,0.00008180959,0.0002447385],"category_scores_gemma":[0.00006380956,0.000169737,0.0004099547,0.001781051,0.00008645205,0.002162842,0.001016432,0.0003486379,0.00004022472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005745903,"about_ca_system_score_gemma":0.0002116432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006203312,"about_ca_topic_score_gemma":0.0000337352,"domain_scores_codex":[0.9975407,0.00009301804,0.001037868,0.0004539983,0.0006236431,0.0002508296],"domain_scores_gemma":[0.9957939,0.0001225577,0.00138145,0.001953341,0.0005264446,0.0002222739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001177677,0.002773196,0.01062164,0.00006232271,0.01617034,0.0005232719,0.003274621,0.003709392,0.0003625245,0.4848575,0.02780365,0.4497238],"study_design_scores_gemma":[0.0009229421,0.0007459162,0.04039383,0.0001313783,0.01303704,0.0004105608,0.0002544803,0.5331237,0.0003755522,0.3326739,0.07682262,0.001108071],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002287528,0.0004829299,0.9928872,0.0008107325,0.0001115235,0.00006269087,0.0001123282,0.00002559154,0.005278258],"genre_scores_gemma":[0.3086821,0.0005211044,0.6900035,0.0003020508,0.0002160763,0.000001229679,0.00005023529,0.00001029556,0.0002133435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5294143,"threshold_uncertainty_score":0.8486089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1643455733332151,"score_gpt":0.3661070833135371,"score_spread":0.201761509980322,"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."}}