{"id":"W1599979262","doi":"10.1111/j.1467-9892.2005.00391.x","title":"Testing Non‐Correlation and Non‐Causality between Multivariate ARMA Time Series","year":2005,"lang":"en","type":"preprint","venue":"Journal of Time Series Analysis","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Univariate; Multivariate statistics; Econometrics; Series (stratigraphy); Mathematics; Causality (physics); Statistics; Granger causality; Generalization; Statistical hypothesis testing","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002267924,0.0006611738,0.003585585,0.001763767,0.0003544336,0.000609334,0.0006177312,0.0004848053,0.002257943],"category_scores_gemma":[0.0003916025,0.0006873708,0.001499436,0.001632317,0.0001595626,0.001105494,0.0007193605,0.0009171647,0.0003285701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002950737,"about_ca_system_score_gemma":0.0001013729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002131846,"about_ca_topic_score_gemma":0.0001120127,"domain_scores_codex":[0.9948044,0.0001106062,0.003522417,0.0008111761,0.0002420906,0.0005092802],"domain_scores_gemma":[0.9920643,0.0002211611,0.006000704,0.0008327195,0.0005687238,0.0003123707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003409342,0.0002823223,0.7936323,0.0005714599,0.04287342,0.00008711441,0.002280127,0.1512463,0.0004135199,0.0005890027,0.002004346,0.00567924],"study_design_scores_gemma":[0.001114471,0.0004742171,0.7771966,0.0003415351,0.009487313,0.00007357631,0.0003027727,0.1864022,0.00006876902,0.007674777,0.01500159,0.001862068],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9303949,0.005765487,0.04264053,0.003719762,0.0007912483,0.0008044588,0.001978091,0.0001238586,0.01378164],"genre_scores_gemma":[0.9616775,0.000402636,0.02296496,0.00004768351,0.001847993,0.00001146781,0.0002372976,0.00009850971,0.01271195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03515597,"threshold_uncertainty_score":0.9995577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02795278520871939,"score_gpt":0.2369765733745631,"score_spread":0.2090237881658437,"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."}}