{"id":"W4312727489","doi":"10.2139/ssrn.4245812","title":"Borrow Now, Pay Even Later: A Quantitative Analysis of Student Debt Payment Plans","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Higher Education Research Studies","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Government of Canada; University of Toronto","funders":"","keywords":"Payment; Debt; Actuarial science; Economics; Student debt; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004677379,0.00009825284,0.0002740133,0.0004244165,0.001246966,0.00004745137,0.0005288463,0.00002288534,0.0006695607],"category_scores_gemma":[0.0001014364,0.00007686199,0.0002020028,0.001478835,0.0001425291,0.0001034161,0.0001165663,0.001062937,0.00001198195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002296535,"about_ca_system_score_gemma":0.003760939,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001260095,"about_ca_topic_score_gemma":0.04199026,"domain_scores_codex":[0.9957973,0.0009124143,0.0003205256,0.0001829588,0.001296155,0.001490628],"domain_scores_gemma":[0.9990696,0.0002540725,0.0002341645,0.0001300635,0.0002054605,0.0001066909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001199308,0.0009110108,0.5610725,0.000005878824,0.009375857,0.000009583848,0.1319763,0.00200936,0.0001848599,0.289416,0.002514417,0.002404345],"study_design_scores_gemma":[0.000914997,0.001449838,0.3102266,0.00001118214,0.001155321,0.000008286788,0.569948,0.0001460581,0.00002850103,0.04107125,0.07462934,0.0004106237],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795226,0.002293202,0.0004488886,0.01462706,0.0003186792,0.0002888817,0.00004553739,0.00002329278,0.002431793],"genre_scores_gemma":[0.9900554,0.003593805,0.0000474099,0.00006562382,0.00007399302,0.0000508437,0.000007470871,0.000008170234,0.006097312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4379717,"threshold_uncertainty_score":0.9754909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235733995301404,"score_gpt":0.3961410281194919,"score_spread":0.3737836881664779,"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."}}