{"id":"W1988954495","doi":"10.5539/ijsp.v4n1p68","title":"The Explicit Solution and Precise Distribution of CKLS Model under Girsanov Transform","year":2015,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing Higher Education Young Elite Teacher Project; China Scholarship Council; National Natural Science Foundation of China","keywords":"Girsanov theorem; Mathematics; Applied mathematics; Order (exchange); Measure (data warehouse); Moment (physics); Distribution (mathematics); Gamma distribution; Relation (database); Inverse-gamma distribution; Mathematical analysis; Computer science; Statistics; Probability distribution; Physics; Stochastic differential equation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007681746,0.0000796628,0.0001440348,0.00002214993,0.00007741791,0.00005211769,0.0001280041,0.00003979062,0.000006791784],"category_scores_gemma":[0.001701636,0.00005655999,0.00003056037,0.00004902853,0.0001664836,0.0001112718,0.00002988814,0.0001055852,4.82444e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009217449,"about_ca_system_score_gemma":0.0001176465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001136687,"about_ca_topic_score_gemma":0.00001565413,"domain_scores_codex":[0.9988058,0.00004407723,0.0005758187,0.00008919623,0.0003979132,0.00008726094],"domain_scores_gemma":[0.9973949,0.0008236433,0.000324054,0.00008534076,0.001257972,0.0001140416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001033957,0.0001077533,0.0001159369,0.00002244532,0.00003697804,4.590784e-7,0.0001555388,0.0001729849,0.00006870204,0.9852194,0.002065934,0.01193043],"study_design_scores_gemma":[0.0005127745,0.00006500482,0.003836855,0.00002466182,0.00003791221,0.00002313043,0.00007942616,0.05189188,0.0001522043,0.9429497,0.0003713192,0.00005519353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04235534,0.00007347415,0.953702,0.002087813,0.00008767218,0.0001524747,0.001355476,0.000005388499,0.0001803581],"genre_scores_gemma":[0.9590484,0.00009937139,0.04071489,0.00001889189,0.00002878247,0.000008080317,0.00004933449,0.000004324756,0.00002795419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.916693,"threshold_uncertainty_score":0.2306449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09290576482567202,"score_gpt":0.3658643819742026,"score_spread":0.2729586171485306,"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."}}