{"id":"W2033548285","doi":"10.1002/env.1108","title":"Statistical inference in Lombard's smooth‐change model","year":2011,"lang":"en","type":"article","venue":"Environmetrics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Statistics Canada; Université du Québec à Trois-Rivières","funders":"","keywords":"Estimator; Econometrics; Inference; Statistics; Variance (accounting); Mathematics; Statistical inference; Robustness (evolution); Computer science; Economics; 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":[0.04752841,0.0008888884,0.003153399,0.003286397,0.001160865,0.002472508,0.003901332,0.002659734,0.003981119],"category_scores_gemma":[0.1927789,0.001019352,0.002465112,0.00317314,0.005513801,0.003180253,0.002856762,0.003689453,0.00056054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001875087,"about_ca_system_score_gemma":0.001597328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01126556,"about_ca_topic_score_gemma":0.00648332,"domain_scores_codex":[0.9711798,0.02043239,0.0007204983,0.00400104,0.00280557,0.0008608283],"domain_scores_gemma":[0.829977,0.1480863,0.006655135,0.01070763,0.003915078,0.0006587493],"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":[0.0009871268,0.0001815415,0.0311314,0.0003591622,0.001234312,0.0007253297,0.001366104,0.2483582,0.001621185,0.5832312,0.003762199,0.1270422],"study_design_scores_gemma":[0.0001074382,0.0002166835,0.007710123,0.0000528995,0.0001323911,0.0001273158,0.0001110625,0.7523974,0.0008361955,0.235889,0.002353026,0.00006643379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04859206,0.0004635299,0.9485545,0.0005625554,0.0000456229,0.0001545242,0.0001575263,0.0003241894,0.001145466],"genre_scores_gemma":[0.6768796,0.0003653635,0.3172011,0.0003577675,0.0001131758,0.0007478263,0.0004809712,0.0001223123,0.00373191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04752841,"threshold_uncertainty_score":0.2513573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3912939287957271,"score_gpt":0.3893539993085515,"score_spread":0.001939929487175529,"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."}}