{"id":"W4315648476","doi":"10.1007/s10463-022-00861-3","title":"Correction to: Group least squares regression for linear models with strongly correlated predictor variables","year":2023,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Mathematics; Statistics; Linear regression; Generalized least squares; Regression; Group (periodic table); Total least squares; Regression analysis; Chemistry","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":[0.0002899843,0.0001329482,0.0002555987,0.00009284323,0.0001177872,0.00002745429,0.0004492746,0.00006051457,0.000004876892],"category_scores_gemma":[0.0004826163,0.00007974312,0.00005859913,0.0004358487,0.0001114698,0.0003288471,0.0001667515,0.00009386068,0.000009517318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007544808,"about_ca_system_score_gemma":0.0000616765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002971534,"about_ca_topic_score_gemma":0.000009139961,"domain_scores_codex":[0.9987918,0.00002930255,0.0003858761,0.0002015303,0.0003903809,0.0002011853],"domain_scores_gemma":[0.9985555,0.0004627384,0.0002282912,0.000364785,0.0003053054,0.00008331938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004454338,0.0008755191,0.00009606271,0.001516603,0.0001817456,0.000008606054,0.002608454,0.1902081,0.004587403,0.6741781,0.1114908,0.01380318],"study_design_scores_gemma":[0.0003249594,0.0003981056,0.0002092466,0.00173784,0.000026771,0.000005173825,0.00009744179,0.9215879,0.005180164,0.0699445,0.0003646546,0.00012328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0298337,0.000007616394,0.9677575,0.0004839323,0.0008518387,0.0004513157,0.0001886462,0.00008487929,0.0003405241],"genre_scores_gemma":[0.5407193,0.00002383888,0.4585473,0.00008568792,0.0000436089,0.00006307383,0.00005102741,0.00001961394,0.0004465508],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7313798,"threshold_uncertainty_score":0.325183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06068453922395285,"score_gpt":0.3102164468924399,"score_spread":0.249531907668487,"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."}}