{"id":"W7130256352","doi":"","title":"A New Linear Estimator for Gaussian Dynamic Term Structure Models","year":2015,"lang":"","type":"article","venue":"Open MIND","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Context (archaeology); Term (time); Gaussian; Variety (cybernetics); Gaussian process; Estimation; Minimax estimator","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000408649,0.0003826018,0.000831004,0.0002451198,0.0003043641,0.0006546738,0.0009584986,0.0004067628,0.00182733],"category_scores_gemma":[0.0001892125,0.0004633871,0.0002201615,0.0003665031,0.00008003252,0.001023544,0.0003225232,0.0002421004,0.0006458177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002944246,"about_ca_system_score_gemma":0.0008396177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003359446,"about_ca_topic_score_gemma":0.0007048553,"domain_scores_codex":[0.997339,0.00001145716,0.001048115,0.0009296507,0.00007475192,0.0005970334],"domain_scores_gemma":[0.9978575,0.0000512159,0.0006231552,0.000748298,0.0001063978,0.0006134878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006524255,0.0003285075,0.007919697,0.00006475528,0.0002635395,0.00001667969,0.008095343,0.02959052,0.00002869565,0.0625184,0.008905956,0.8816155],"study_design_scores_gemma":[0.003608848,0.000341365,0.006051948,0.00007639764,0.00007696386,0.00001312051,0.0002697508,0.6239929,0.00004039393,0.0781448,0.2865312,0.0008523546],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3820163,0.004952399,0.5613565,0.002880978,0.005008758,0.004390518,0.01169043,0.000008054204,0.02769606],"genre_scores_gemma":[0.7958068,0.00008895378,0.1824299,0.00001674125,0.0006948559,0.00003310653,0.0003441863,0.00007705111,0.02050841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8807631,"threshold_uncertainty_score":0.9997818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08926066754691742,"score_gpt":0.3130821759394315,"score_spread":0.2238215083925141,"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."}}