{"id":"W4416776755","doi":"10.1016/j.frl.2025.109132","title":"Commercial paper digitisation and corporate debt default risk:Evidence and mechanism from China","year":2025,"lang":"en","type":"article","venue":"Finance research letters","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"National Social Science Fund of China; Major Program of National Fund of Philosophy and Social Science of China; Sichuan Office of Philosophy and Social Science","keywords":"Debt; Exploit; China; Digitization; Default; Shock (circulatory); Mechanism (biology); Credit risk; Capital requirement; Capital (architecture)","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":[0.002026441,0.0002281196,0.0004429855,0.004900778,0.001321756,0.002577784,0.000842717,0.0007317913,0.009454456],"category_scores_gemma":[0.008531732,0.0002178516,0.000395271,0.007670421,0.001681903,0.001440129,0.001286138,0.0006151467,0.0006002128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002363611,"about_ca_system_score_gemma":0.001710453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03661698,"about_ca_topic_score_gemma":0.03786211,"domain_scores_codex":[0.9987493,0.0001752271,0.0001397648,0.0002500723,0.0004610776,0.0002245245],"domain_scores_gemma":[0.9802749,0.004111812,0.009823757,0.002446966,0.001971909,0.001370744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003404064,0.0001434977,0.9433691,0.0001406231,0.0001307593,0.0006680919,0.001552204,0.0004569073,0.0007105635,0.003538104,0.002963461,0.04598631],"study_design_scores_gemma":[0.0000409886,0.00007360506,0.9917462,0.00004236169,0.0001549319,0.0002110783,0.0007099044,0.0007234246,0.0006322052,0.0009473971,0.004701243,0.00001660234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874537,0.002399835,0.0002593547,0.0006234241,0.00001726773,0.00003684482,0.0009049871,0.00003005114,0.008274571],"genre_scores_gemma":[0.9954023,0.0009583198,0.00007626396,0.00007936462,0.0000432222,0.000008157584,0.0006034371,0.000004779798,0.002824167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03661698,"threshold_uncertainty_score":0.07280767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05841742250006515,"score_gpt":0.2871034828648617,"score_spread":0.2286860603647966,"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."}}