{"id":"W1494864831","doi":"","title":"An Empirical Investigation of Collateral and Sorting in the HELOC Market","year":2004,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Collateral; Collateralized debt obligation; Loan; Credit risk; Economics; Sorting; Interest rate; Actuarial science; Financial economics; Business; Monetary economics; Finance; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00232485,0.0001429342,0.0005102849,0.001361564,0.0005627568,0.001681276,0.0004767931,0.0006526921,0.01057984],"category_scores_gemma":[0.02947023,0.0001352492,0.0002103565,0.002318619,0.00134346,0.004152765,0.001128349,0.0007910513,0.0008495682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004664677,"about_ca_system_score_gemma":0.0004587161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357393,"about_ca_topic_score_gemma":0.001084041,"domain_scores_codex":[0.998911,0.0004368334,0.0001021108,0.0001454613,0.000266951,0.0001374848],"domain_scores_gemma":[0.9649958,0.0170926,0.01294477,0.001767552,0.001546963,0.001652215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006010086,0.000504314,0.8906394,0.00009870104,0.00008919414,0.0004810587,0.002195919,0.005489456,0.001299122,0.0521324,0.001631091,0.04483821],"study_design_scores_gemma":[0.0001448843,0.0005722718,0.8669198,0.000106185,0.00007157154,0.0007050464,0.004613186,0.0444721,0.00186569,0.07302181,0.007437817,0.00006955805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921543,0.0002165525,0.00218556,0.0002871764,0.000004277174,0.00003124894,0.0002129424,0.00002226741,0.004885743],"genre_scores_gemma":[0.9988336,0.00006196707,0.0002792762,0.00001963016,0.00001219702,0.000006136519,0.0001456991,0.000003878245,0.0006377913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01057984,"threshold_uncertainty_score":0.03539306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04901775349652086,"score_gpt":0.3190739416723964,"score_spread":0.2700561881758755,"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."}}