{"id":"W4408305596","doi":"10.2139/ssrn.5100828","title":"&lt;span&gt;Fragility of Green Financing: Evidence from Proprietary Loan Assessment Data&lt;/span&gt;","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Span (engineering); Loan; Fragility; Economics; Finance; Engineering; Structural engineering; Physics","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":[0.002988031,0.0002021508,0.0003070292,0.003801203,0.0005329542,0.002122425,0.0008203181,0.001336015,0.01433786],"category_scores_gemma":[0.02845055,0.0002490511,0.0004009771,0.006058004,0.0008980493,0.002883527,0.001039859,0.000843389,0.002553955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092753,"about_ca_system_score_gemma":0.0007666657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01790475,"about_ca_topic_score_gemma":0.02701931,"domain_scores_codex":[0.9983046,0.0004403522,0.0001504644,0.0001985555,0.0007418277,0.0001642133],"domain_scores_gemma":[0.9464909,0.0248623,0.01954925,0.003056704,0.004929529,0.001111293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008557799,0.0002192633,0.6714248,0.0002776586,0.0003377902,0.0007370076,0.001333285,0.004423961,0.0006863779,0.0293484,0.1602014,0.1301542],"study_design_scores_gemma":[0.00008560094,0.0001926161,0.866356,0.0004271066,0.0001721414,0.0002883477,0.001924251,0.01106862,0.004985907,0.04036443,0.07401516,0.0001198309],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8564795,0.004035403,0.004842781,0.02154251,0.0002093706,0.00009437252,0.05988269,0.0003343812,0.05257886],"genre_scores_gemma":[0.9638789,0.002156201,0.001064212,0.0009245941,0.0001902973,0.00005832676,0.01528768,0.0001049945,0.01633483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01790475,"threshold_uncertainty_score":0.04796493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393652217478706,"score_gpt":0.2554719817994255,"score_spread":0.2161067600515549,"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."}}