{"id":"W7039597926","doi":"","title":"A numerical study of penalized regression","year":2013,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Elastic net regularization; Lasso (programming language); Focus (optics); Linear regression; Regression; Correlation; Regression analysis; Proper linear model","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":[0.001456619,0.0001872208,0.0006002664,0.0006905348,0.0002354159,0.00009266341,0.001846527,0.0001188312,0.0002704053],"category_scores_gemma":[0.0004631624,0.0001690857,0.0001858571,0.0009830842,0.0000658959,0.0002451251,0.0003746986,0.0001790669,0.0003482612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000421363,"about_ca_system_score_gemma":0.00006399324,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005714499,"about_ca_topic_score_gemma":0.04194821,"domain_scores_codex":[0.9962792,0.0003026742,0.000348675,0.0007645608,0.002118524,0.0001863371],"domain_scores_gemma":[0.9966033,0.0003456434,0.001056632,0.001298934,0.0006026199,0.00009293377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001135952,0.003237772,0.06696812,0.0002791686,0.0004083532,0.0001395268,0.01612012,0.0007610908,0.0007430096,0.0005363091,0.8197205,0.08995009],"study_design_scores_gemma":[0.001516126,0.0004498021,0.5388172,0.0002405683,0.0001740741,0.000001084588,0.4357333,0.004912994,0.00008619549,0.0005721262,0.01715479,0.0003417576],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988268,0.00004943432,0.0006986883,0.0001277045,0.001014348,0.0004736251,0.0000120904,0.00003177462,0.009324322],"genre_scores_gemma":[0.973253,0.000007276594,0.0006958189,0.000004846675,0.00002509147,3.735158e-7,0.0000795303,0.00001011305,0.02592395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8025657,"threshold_uncertainty_score":0.9755337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.076615698303175,"score_gpt":0.3237691613858428,"score_spread":0.2471534630826678,"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."}}