{"id":"W4414113890","doi":"10.1111/iere.70080","title":"College Loans and Human Capital Investment","year":2025,"lang":"en","type":"article","venue":"International Economic Review","topic":"Higher Education Research Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Human capital; Loan; Investment (military); Government (linguistics); Student loan; Welfare; Revenue","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001159681,0.0002086514,0.0003532446,0.0007461812,0.0003015987,0.002425739,0.0004393277,0.0007105857,0.01353963],"category_scores_gemma":[0.006942838,0.0001617542,0.0002871184,0.001702911,0.0008816503,0.0009955748,0.000884129,0.0009647535,0.0007446173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002829714,"about_ca_system_score_gemma":0.001824163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01589,"about_ca_topic_score_gemma":0.01220379,"domain_scores_codex":[0.9993572,0.0002315202,0.00003613891,0.00009943944,0.0001030513,0.0001727894],"domain_scores_gemma":[0.9918792,0.00333773,0.003304131,0.0002372121,0.0004576475,0.0007841471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004918657,0.0004913573,0.4883752,0.0006993719,0.0003995029,0.0004239835,0.0007427267,0.1459439,0.0006085128,0.2453405,0.02603754,0.0904457],"study_design_scores_gemma":[0.0002409069,0.000424739,0.6102862,0.0008387702,0.0003628498,0.0002509947,0.002119418,0.1298507,0.001224905,0.1995599,0.05473262,0.0001079225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9094558,0.01089988,0.005285072,0.009536051,0.00008240345,0.00009561631,0.003205596,0.0001059243,0.0613336],"genre_scores_gemma":[0.9937049,0.00193838,0.0002454843,0.0001072593,0.00004330518,0.00001800286,0.0003824832,0.000004119902,0.003556018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01589,"threshold_uncertainty_score":0.04529464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03534386987604847,"score_gpt":0.4230883722942212,"score_spread":0.3877445024181728,"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."}}