{"id":"W3122578905","doi":"10.1142/s2010007817500063","title":"EMPIRICALLY CONSTRAINED CLIMATE SENSITIVITY AND THE SOCIAL COST OF CARBON","year":2017,"lang":"en","type":"preprint","venue":"Climate Change Economics","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Fraser Institute","funders":"","keywords":"Climate sensitivity; Sensitivity (control systems); Monte Carlo method; Econometrics; Climate change; Dice; Environmental science; Climate model; Social cost; Quantile; Economics; Climatology; Mathematics; Statistics; Ecology; Engineering; Geology","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":[0.003248889,0.0007139135,0.002483552,0.0003160353,0.0006673879,0.0004361614,0.0006969657,0.0008389803,0.0001203424],"category_scores_gemma":[0.0002205389,0.0007629101,0.0005868917,0.00005229674,0.001706918,0.0002479647,0.002474934,0.0008083108,0.00008453344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003036377,"about_ca_system_score_gemma":0.00005556434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001504314,"about_ca_topic_score_gemma":0.001788574,"domain_scores_codex":[0.995886,0.00009540768,0.001773275,0.001166205,0.00003527055,0.00104388],"domain_scores_gemma":[0.9944708,0.0003934363,0.003595733,0.001279623,0.00007470266,0.0001856769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001061131,0.0002685762,0.08067029,0.002693047,0.0007635034,0.00002534103,0.01644581,0.0001257988,0.000008145211,0.8915877,0.0002917131,0.006058937],"study_design_scores_gemma":[0.03451439,0.0004290119,0.1668011,0.001638917,0.001237485,0.0002907313,0.006551449,0.3038292,0.0003300627,0.4410188,0.03252357,0.01083528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9131788,0.002508093,0.00001572668,0.009474709,0.002628513,0.002089669,0.02274111,0.0000864989,0.04727686],"genre_scores_gemma":[0.9556201,0.04092997,0.0001229674,0.0008312632,0.001544767,0.0003563645,0.0004338338,0.000129761,0.00003099088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4505689,"threshold_uncertainty_score":0.9994822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1970304283651394,"score_gpt":0.3132287358658429,"score_spread":0.1161983075007035,"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."}}