{"id":"W4312332703","doi":"10.1007/978-3-031-13971-0_15","title":"A Generalized Quadratic Garrote Approach Towards Ridge Regression Analysis","year":2022,"lang":"en","type":"book-chapter","venue":"Emerging topics in statistics and biostatistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Multicollinearity; Regression; Regression analysis; Lasso (programming language); Mathematics; Ridge; Collinearity; Linear regression; Shrinkage; Polynomial regression; Estimator; Quadratic equation; Statistics; Applied mathematics; Segmented regression; Local regression; Computer science; Geology; Geometry","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":[0.002660718,0.001207872,0.001192795,0.0009270271,0.0004665611,0.001201399,0.001821951,0.001237698,0.005813297],"category_scores_gemma":[0.006160216,0.0007863767,0.001253574,0.001753248,0.001244704,0.001532554,0.001880752,0.002934064,0.004102105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002707224,"about_ca_system_score_gemma":0.0006263099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00090164,"about_ca_topic_score_gemma":0.001877055,"domain_scores_codex":[0.9979737,0.0009375036,0.00008554808,0.0002842433,0.0006624638,0.00005652188],"domain_scores_gemma":[0.9981535,0.0007239375,0.00009759577,0.000563941,0.0004064684,0.00005451016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001230308,0.0001195046,0.0005251925,0.0003349421,0.0002059182,0.0002254581,0.0001848781,0.1080699,0.02132378,0.3518901,0.02030677,0.4966905],"study_design_scores_gemma":[0.00002118723,0.0001004096,0.0004908605,0.0000632429,0.0000632233,0.0002962469,0.00003404207,0.6919119,0.00645481,0.2547351,0.04576677,0.00006210994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005179335,0.0001851018,0.9982685,0.00004788218,0.00004734948,0.000006158853,0.00002442576,0.0001674156,0.00073535],"genre_scores_gemma":[0.02240743,0.0007816105,0.9630015,0.0001716706,0.0002197043,0.00007197705,0.0002527407,0.0006174936,0.01247582],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005813297,"threshold_uncertainty_score":0.01944745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1189967252573367,"score_gpt":0.4101478682463008,"score_spread":0.2911511429889641,"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."}}