{"id":"W869473736","doi":"10.5351/ckss.2009.16.1.041","title":"Seasonal Adjustment on Chain-Linking","year":2009,"lang":"en","type":"article","venue":"Communications for Statistical Applications and Methods","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Seasonality; Chain (unit); Econometrics; Seasonal adjustment; Quarter (Canadian coin); Volume (thermodynamics); Economics; Statistics; Environmental science; Mathematics; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000609476,0.0001139312,0.0002864574,0.0001071172,0.0003609859,0.00004424915,0.0003454903,0.00005915774,0.00005482721],"category_scores_gemma":[0.0000862173,0.0001222084,0.00008148282,0.000142572,0.0001350212,0.00004760441,0.00005662389,0.0001119057,0.00005642471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005529316,"about_ca_system_score_gemma":0.00001453507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001825315,"about_ca_topic_score_gemma":0.000003850846,"domain_scores_codex":[0.9990246,0.00003877433,0.0004366225,0.0003125442,0.00002044181,0.0001669743],"domain_scores_gemma":[0.9981727,0.0007541621,0.0001624669,0.0007557962,0.00004183414,0.0001130563],"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":[0.000005574871,0.00009502516,0.00007396321,0.000004632575,0.00002067501,1.608939e-8,0.00002576484,0.00001411607,0.000006732262,0.7308782,0.0002215334,0.2686538],"study_design_scores_gemma":[0.0002032622,0.00007296616,0.005213915,0.000004998415,0.00001817132,0.000001055767,0.00002179133,0.05480108,0.00000608983,0.6074147,0.3321111,0.0001308034],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008899719,0.002266375,0.9760553,0.005808245,0.00002563402,0.0004416805,0.0003678493,0.00002909153,0.01491686],"genre_scores_gemma":[0.1231216,0.001310406,0.8727099,0.0012329,0.00007897302,0.000678038,0.0003255636,0.00001199195,0.0005306971],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3318896,"threshold_uncertainty_score":0.4983516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08355609058846013,"score_gpt":0.3737072205541622,"score_spread":0.2901511299657021,"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."}}