{"id":"W7107945645","doi":"10.3886/e240746v2","title":"Datasets and code for Systemic Financial Risks of Climate Shocks: Empirical Evidence from Major Free-Floating Currencies","year":2025,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Empirical evidence; Liberian dollar; Volatility (finance); Code (set theory); Financial market; Empirical research; Us dollar","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001115536,0.0008992502,0.0006635244,0.002011083,0.0005819249,0.001602423,0.001794433,0.001534794,0.0641209],"category_scores_gemma":[0.006822543,0.0004517858,0.0007438287,0.003944674,0.000294443,0.001177066,0.001578695,0.001814297,0.05537412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009983592,"about_ca_system_score_gemma":0.001591957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02653093,"about_ca_topic_score_gemma":0.03825543,"domain_scores_codex":[0.9994035,0.0001208463,0.00009859989,0.0001346329,0.0001458374,0.00009654583],"domain_scores_gemma":[0.9978701,0.0006522001,0.0003400344,0.0004466964,0.0005187672,0.0001721265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004020826,0.00003090366,0.002246134,0.0002207001,0.00001907063,0.00002800532,0.00002951234,0.0007720079,0.00005763711,0.00118527,0.9929223,0.002448312],"study_design_scores_gemma":[0.0003055056,0.00001935615,0.01084454,0.0003223156,0.00002169778,0.00008174915,0.0001954993,0.001975211,0.0002979335,0.004342592,0.9815431,0.00005042691],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002785946,0.00002587765,0.0001392083,0.00009085368,0.00001762682,0.00001615102,0.9986591,0.0002217302,0.000550859],"genre_scores_gemma":[0.001222056,0.00004646825,0.0008288319,0.00007556754,0.00001111627,0.0001608433,0.9968137,0.00009261431,0.0007487404],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0641209,"threshold_uncertainty_score":0.2145057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2238538170338048,"score_gpt":0.4219951845463241,"score_spread":0.1981413675125193,"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."}}