{"id":"W7097301283","doi":"","title":"ON PERIODIC AUTOGRESSIVE CONDITIONAL HETEROSKEDASTICITY","year":2011,"lang":"en","type":"article","venue":"","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Corporation; Private sector; Public policy; Government (linguistics); Product (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06487952,0.003686285,0.007940357,0.004818363,0.002722246,0.006226887,0.007036827,0.004328365,0.0660703],"category_scores_gemma":[0.1498539,0.002668331,0.006650456,0.007356491,0.00594332,0.008478041,0.005077187,0.008062823,0.0106713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00415245,"about_ca_system_score_gemma":0.007339349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03962229,"about_ca_topic_score_gemma":0.03046395,"domain_scores_codex":[0.9401762,0.0383083,0.002574396,0.01111152,0.004815035,0.00301436],"domain_scores_gemma":[0.6968645,0.2563363,0.01545069,0.02084852,0.00896747,0.001532463],"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":[0.001296816,0.0005572843,0.0422223,0.002565136,0.007934465,0.004045853,0.00181054,0.1685309,0.0007531072,0.5591447,0.06076616,0.1503728],"study_design_scores_gemma":[0.000551111,0.0007107599,0.01255089,0.0007766088,0.001191386,0.0005612844,0.001082033,0.4345485,0.001117514,0.512689,0.0337973,0.0004236377],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03410879,0.005183538,0.9254989,0.005696642,0.001625695,0.001345744,0.007059616,0.003125303,0.01635581],"genre_scores_gemma":[0.7399846,0.008380573,0.1570687,0.002765201,0.002380569,0.003695486,0.01114382,0.00133009,0.07325083],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0660703,"threshold_uncertainty_score":0.3431198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04794354437869876,"score_gpt":0.2373960900614801,"score_spread":0.1894525456827813,"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."}}