{"id":"W4401691616","doi":"10.2139/ssrn.4930243","title":"Carbon Risk and Trade Credit","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Business; Carbon fibers; Credit risk; Economics; Financial system; Materials science; Actuarial science; Composite material","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":[0.0006082307,0.0003343477,0.0004740694,0.0009941766,0.0004969417,0.003052209,0.0003073918,0.002359267,0.0155416],"category_scores_gemma":[0.006608725,0.0001831293,0.0002713155,0.001552503,0.001118039,0.0032691,0.0007073251,0.001839772,0.0007587904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125398,"about_ca_system_score_gemma":0.0005579905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003270917,"about_ca_topic_score_gemma":0.002375504,"domain_scores_codex":[0.9998134,0.00006009687,0.0000118473,0.00003745833,0.0000505707,0.00002672404],"domain_scores_gemma":[0.997327,0.001484978,0.0005964424,0.0001612207,0.0002380959,0.0001921489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001938208,0.0001324649,0.01481699,0.0001451901,0.00006548396,0.0004830901,0.0001622057,0.0384812,0.0004382,0.8924398,0.01703098,0.03561066],"study_design_scores_gemma":[0.00001743156,0.00001245525,0.00343784,0.00004883905,0.00001409183,0.00008428127,0.00007906823,0.02284723,0.0001330422,0.967066,0.006245648,0.00001408758],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6150663,0.0335419,0.03880413,0.05741237,0.001586251,0.00004350199,0.001646869,0.0002667351,0.2516318],"genre_scores_gemma":[0.9746459,0.004172861,0.0004417279,0.0002360725,0.0006234027,0.000007279816,0.000141999,0.00002320654,0.01970755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0155416,"threshold_uncertainty_score":0.05199188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02252574966789113,"score_gpt":0.2027540603613466,"score_spread":0.1802283106934555,"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."}}