{"id":"W3107871550","doi":"10.1038/s41561-020-00663-3","title":"Opportunities and challenges in using remaining carbon budgets to guide climate policy","year":2020,"lang":"en","type":"article","venue":"Nature Geoscience","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":142,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University; Environment and Climate Change Canada; Simon Fraser University; Concordia University","funders":"Horizon 2020 Framework Programme; Concordia University; Natural Sciences and Engineering Research Council of Canada; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Gordon and Betty Moore Foundation; Met Office; Simon Fraser University; Department for Environment, Food and Rural Affairs, UK Government; National Science Foundation","keywords":"Limiting; Climate policy; Carbon fibers; Climate change; Environmental science; Carbon price; Natural resource economics; Global warming; Economics; Computer science; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02992926,0.001363674,0.001663824,0.002952668,0.001248624,0.01118046,0.003037867,0.003653328,0.006675739],"category_scores_gemma":[0.08370465,0.0007182265,0.0006363267,0.003179476,0.002190823,0.01436225,0.003124336,0.005462188,0.001494282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003605819,"about_ca_system_score_gemma":0.01317059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03207967,"about_ca_topic_score_gemma":0.04042622,"domain_scores_codex":[0.9897609,0.007284246,0.0005436592,0.0006989333,0.001147153,0.0005649477],"domain_scores_gemma":[0.9479191,0.03382822,0.003684695,0.00298544,0.009436445,0.002146059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003167454,0.000707932,0.02878056,0.001003948,0.0004498143,0.0001556693,0.001187543,0.2299442,0.0009405787,0.301967,0.04830773,0.3862383],"study_design_scores_gemma":[0.00005448538,0.00009049794,0.004035871,0.0009240152,0.00006256725,0.00004062578,0.002519877,0.221314,0.0007640048,0.7094845,0.06060013,0.0001095174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1180882,0.01828713,0.4076183,0.3181102,0.002572625,0.0004144802,0.003413698,0.001764874,0.1297306],"genre_scores_gemma":[0.7442116,0.01081795,0.2310934,0.005821767,0.001037124,0.0003201094,0.001109259,0.0004114318,0.005177484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03207967,"threshold_uncertainty_score":0.158283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3374877851293703,"score_gpt":0.3168980902907451,"score_spread":0.02058969483862522,"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."}}