{"id":"W3027420058","doi":"10.34989/sdp-2020-3","title":"Scenario Analysis and the Economic and Financial Risks from Climate Change","year":2020,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Climate change; Political economy of climate change; Economic analysis; Economics; Economic model; Scenario analysis; Low-carbon economy; Natural resource economics; Business; Finance; Macroeconomics; Agricultural economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002931334,0.000575207,0.002057808,0.001068083,0.0003914565,0.0006418072,0.0008405229,0.0007172145,0.000284105],"category_scores_gemma":[0.0004393947,0.0006219207,0.0004611026,0.0002314076,0.0009552898,0.0002542225,0.002963287,0.001859866,0.0001329892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009631497,"about_ca_system_score_gemma":0.0001289815,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01334569,"about_ca_topic_score_gemma":0.01098244,"domain_scores_codex":[0.9951275,0.0001720567,0.001570901,0.001964695,0.00005252296,0.001112307],"domain_scores_gemma":[0.9967161,0.0009167739,0.0007863867,0.001199873,0.00002468401,0.0003561687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001944919,0.0001988185,0.6433487,0.000700006,0.002949638,0.00006463413,0.01996905,0.003491166,0.000003513153,0.2053987,0.0001977421,0.1217332],"study_design_scores_gemma":[0.006486582,0.0001387379,0.4099251,0.0001910784,0.0003436245,0.000009682778,0.001235592,0.3018991,0.00001403846,0.2451579,0.03231622,0.002282243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9509616,0.004298474,0.00001266838,0.006825398,0.0008234701,0.001562151,0.006816266,0.00005855412,0.02864134],"genre_scores_gemma":[0.8444517,0.152324,0.0002678187,0.000933746,0.001051835,0.0005189849,0.000291844,0.00008838019,0.00007166894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.298408,"threshold_uncertainty_score":0.9996232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1705834250387042,"score_gpt":0.3360467646338602,"score_spread":0.165463339595156,"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."}}