{"id":"W1999209770","doi":"10.1002/cjs.11169","title":"Statistical inference for multivariate partially linear regression models","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Estimator; Nonparametric statistics; Multivariate statistics; Statistical inference; Statistics; Mathematics; Asymptotic distribution; Nonparametric regression; Inference; Parametric statistics; Statistical hypothesis testing; Linear regression; Econometrics; Linear model; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.019353,0.001069718,0.002327441,0.001789124,0.0006191414,0.001793015,0.002366717,0.001175868,0.002682102],"category_scores_gemma":[0.1018796,0.0007786564,0.001851863,0.002688597,0.002087792,0.002096127,0.001769739,0.002390059,0.0003276321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445397,"about_ca_system_score_gemma":0.002409824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007556282,"about_ca_topic_score_gemma":0.005216606,"domain_scores_codex":[0.9831197,0.01270039,0.000436358,0.00156099,0.001840158,0.0003425568],"domain_scores_gemma":[0.9147607,0.0737334,0.005087357,0.003275139,0.002809465,0.0003339139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001544548,0.0001063961,0.008788281,0.0004058586,0.0007707541,0.0002797832,0.0001955761,0.5818977,0.000800492,0.3122864,0.002476883,0.09183747],"study_design_scores_gemma":[0.00001706263,0.0000381406,0.0008151854,0.00002992548,0.00003732857,0.00003454772,0.00001986426,0.8851077,0.0001767389,0.1130955,0.0006144951,0.00001345679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009078181,0.0003408397,0.9895278,0.0003277207,0.00002745404,0.00003005544,0.0001159559,0.0001478667,0.0004040884],"genre_scores_gemma":[0.6468275,0.001462036,0.3467845,0.0004330383,0.0004421553,0.00053107,0.001038727,0.0001230444,0.002358068],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.019353,"threshold_uncertainty_score":0.1023497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1612147932264194,"score_gpt":0.4182351788411224,"score_spread":0.2570203856147031,"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."}}