{"id":"W6947723673","doi":"10.3886/e226141v1","title":"Dataset on the Impact of Climate Shocks on US Dollar Volatility Against Major Currencies","year":2025,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Currency; Exchange rate; Liberian dollar; Volatility (finance); Us dollar; Financial market; Climate change; Event (particle physics)","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":[0.0006635114,0.0008731002,0.0006402817,0.002374551,0.0004381034,0.001210416,0.001268503,0.001160915,0.01871576],"category_scores_gemma":[0.003923744,0.0002545534,0.0006424641,0.005246275,0.0001980478,0.0007213624,0.001022836,0.001043279,0.0174733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008011471,"about_ca_system_score_gemma":0.001166836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02553196,"about_ca_topic_score_gemma":0.03671572,"domain_scores_codex":[0.9994475,0.00008682959,0.00009696847,0.0001315476,0.0001625044,0.00007456609],"domain_scores_gemma":[0.9986066,0.00034989,0.0002636649,0.0001992313,0.0004689236,0.0001117],"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":[0.00006816816,0.00004843029,0.007764984,0.0003676627,0.00005738649,0.00005986031,0.00003264975,0.001130698,0.000125428,0.001023751,0.9843028,0.005018253],"study_design_scores_gemma":[0.000281558,0.0000484764,0.05452973,0.0004111525,0.00005235554,0.0001854553,0.0002454015,0.003706997,0.0005674933,0.002108819,0.9377979,0.00006467488],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009017804,0.00007689858,0.00006025303,0.00009174645,0.00002134295,0.000007596004,0.9980958,0.0001129864,0.000631668],"genre_scores_gemma":[0.001956257,0.00005315672,0.0001924879,0.00003983495,0.000008557038,0.00003538408,0.9973752,0.00001287269,0.0003262299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02553196,"threshold_uncertainty_score":0.06261051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05344103273657141,"score_gpt":0.3275827596080193,"score_spread":0.2741417268714479,"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."}}