{"id":"W2146414774","doi":"10.1111/j.1467-842x.2010.00596.x","title":"A QUASI‐LOCALLY MOST POWERFUL TEST FOR CORRELATION IN THE CONDITIONAL VARIANCE OF POSITIVE DATA","year":2011,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Statistics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Autocorrelation; Statistics; Conditional variance; Variance (accounting); Robustness (evolution); Econometrics; Correlation; Autoregressive conditional heteroskedasticity","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006465593,0.00009468616,0.0003538067,0.0001325812,0.00003838171,0.00003370269,0.0003568909,0.000048635,0.0004149604],"category_scores_gemma":[0.0002688915,0.00008108406,0.00005605728,0.0001972478,0.00005132457,0.0002125223,0.00002140766,0.0001300941,0.00001378634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002912772,"about_ca_system_score_gemma":0.00007370325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001471063,"about_ca_topic_score_gemma":0.0003184498,"domain_scores_codex":[0.9986814,0.00001991351,0.0009458001,0.0001377823,0.00006983168,0.0001452838],"domain_scores_gemma":[0.9981779,0.0003370057,0.001056705,0.0002275617,0.0001418014,0.00005903868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003319709,0.000991291,0.1981984,0.00007124262,0.0004348179,0.00006931921,0.004374606,0.0004111604,0.00001549295,0.5313331,0.2622141,0.001554464],"study_design_scores_gemma":[0.003007059,0.002405917,0.6876637,0.0001474699,0.0001629975,0.0001780763,0.0009114188,0.00810685,0.00001231769,0.2312885,0.0657859,0.0003297875],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01409787,0.0004207013,0.9461641,0.003213598,0.0006420784,0.0006223859,0.03241365,0.000005468386,0.002420201],"genre_scores_gemma":[0.9741096,0.00006033353,0.02190895,0.00008595526,0.0001671929,0.000001276161,0.0003760594,0.0000122905,0.003278285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9600118,"threshold_uncertainty_score":0.4543525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07490927700060995,"score_gpt":0.2657033672796466,"score_spread":0.1907940902790366,"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."}}