{"id":"W2160379884","doi":"10.7202/600931ar","title":"Analyse spectrale des filtres de la méthode de désaisonnalisation X-11-ARMMI","year":2009,"lang":"en","type":"article","venue":"L Actualité économique","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Autoregressive integrated moving average; Seasonality; Seasonal adjustment; Series (stratigraphy); Mathematics; Estimator; Econometrics; Statistics; Time series; Geology; Mathematical analysis; Variable (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01330108,0.001633698,0.0009700177,0.001427218,0.0006942631,0.001704134,0.001203282,0.001326373,0.007109604],"category_scores_gemma":[0.06562895,0.0005429169,0.001014151,0.0007276304,0.001013417,0.001706077,0.001177678,0.004120901,0.002026517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136045,"about_ca_system_score_gemma":0.001212139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007060411,"about_ca_topic_score_gemma":0.005680224,"domain_scores_codex":[0.9932604,0.004307752,0.000223701,0.0006770898,0.001299346,0.0002316871],"domain_scores_gemma":[0.9438082,0.04957323,0.001204299,0.002113802,0.002918834,0.0003816085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002272001,0.0002917417,0.01512737,0.0005525419,0.0005791357,0.0002993773,0.001022101,0.2238437,0.02800695,0.06178617,0.0027786,0.6634403],"study_design_scores_gemma":[0.00008443123,0.0003182441,0.007285413,0.0000788974,0.00005051057,0.0001612191,0.0001643197,0.9650971,0.01198122,0.008097062,0.00662752,0.00005403223],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04132812,0.0004461124,0.9556698,0.0002283614,0.000121478,0.00007558433,0.000136848,0.0008299657,0.001163694],"genre_scores_gemma":[0.2890236,0.00081963,0.6999139,0.0001596341,0.0002188692,0.0007294735,0.0009035078,0.0007733678,0.007458085],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01330108,"threshold_uncertainty_score":0.07034367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0483485733290397,"score_gpt":0.2801375771023641,"score_spread":0.2317890037733244,"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."}}