{"id":"W4236332090","doi":"10.22215/etd/2019-13659","title":"Frequency Domain Tests for Assessing Dependency Characteristics of Stationary Time Series via Tapering","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Tapering; Series (stratigraphy); Statistics; Mathematics; Statistical hypothesis testing; Dependency (UML); Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.005411251,0.0005564982,0.0005728492,0.004561556,0.0004167381,0.001009316,0.0008839774,0.0007356527,0.004101092],"category_scores_gemma":[0.04701583,0.0002110124,0.0006566306,0.002410569,0.0009450336,0.001929735,0.0009764294,0.001241284,0.0009125464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002460198,"about_ca_system_score_gemma":0.0004760632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003959606,"about_ca_topic_score_gemma":0.0003518612,"domain_scores_codex":[0.9970524,0.001283466,0.0003039297,0.0003426849,0.0008985571,0.0001189468],"domain_scores_gemma":[0.9449793,0.04291492,0.004824663,0.003901972,0.002805837,0.000573345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008832782,0.0004200263,0.08025458,0.0005895573,0.0006631602,0.0006760252,0.0005397237,0.04987426,0.04863968,0.09147114,0.004330842,0.7216578],"study_design_scores_gemma":[0.0002361149,0.002077681,0.1935598,0.0002910526,0.000344351,0.001999714,0.0006052136,0.5811689,0.05105914,0.1580209,0.01024451,0.0003925167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1087784,0.000538746,0.8828065,0.0001957572,0.00007272176,0.0001507183,0.0009735415,0.001028798,0.005454757],"genre_scores_gemma":[0.752756,0.0005497842,0.2424854,0.0001691322,0.0002627198,0.0003839624,0.001836668,0.000259907,0.001296386],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005411251,"threshold_uncertainty_score":0.0286178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01832425034517347,"score_gpt":0.2423021392862795,"score_spread":0.223977888941106,"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."}}