{"id":"W2073303950","doi":"10.3905/jfi.2000.319236","title":"Anatomy of Prepayments","year":2000,"lang":"en","type":"article","venue":"The Journal of Fixed Income","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smiths Detection (Canada)","funders":"","keywords":"Prepayment of loan; Equity (law); Demographics; Econometrics; Computer science; Actuarial science; Economics; Finance","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":[0.002395649,0.0009609226,0.0007129908,0.001627137,0.001663961,0.005513469,0.003191768,0.002634134,0.03775873],"category_scores_gemma":[0.009802849,0.00107144,0.00190287,0.002191152,0.001964915,0.01076188,0.003678518,0.004688336,0.012108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002037595,"about_ca_system_score_gemma":0.001689266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003317505,"about_ca_topic_score_gemma":0.001147217,"domain_scores_codex":[0.9979857,0.0004678055,0.0001756877,0.0005016619,0.0006061097,0.0002628991],"domain_scores_gemma":[0.9966403,0.0009875464,0.0004061743,0.001029267,0.000740687,0.0001960115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009300347,0.00003731781,0.001748752,0.00008724012,0.00002024155,0.0004927542,0.0003213124,0.013652,0.000642128,0.9218104,0.00905322,0.05204152],"study_design_scores_gemma":[0.0000248524,0.0001268462,0.002159358,0.0002001241,0.00003934488,0.001963375,0.0002309899,0.06763487,0.002196731,0.7338867,0.1914611,0.00007562373],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02846152,0.004234544,0.8036904,0.004147009,0.0007137076,0.000238211,0.001746008,0.002233878,0.1545347],"genre_scores_gemma":[0.5963101,0.01027206,0.2283107,0.0009398503,0.0009121082,0.0005759796,0.00287418,0.001640211,0.1581648],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03775873,"threshold_uncertainty_score":0.1263155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01620576468131471,"score_gpt":0.2301603395224968,"score_spread":0.213954574841182,"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."}}