{"id":"W2275912048","doi":"10.1038/nclimate2868","title":"Differences between carbon budget estimates unravelled","year":2016,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":295,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"International Institute for Applied Systems Analysis; Natural Environment Research Council; Sight Research UK","keywords":"Greenhouse gas; Limiting; Global warming; Environmental science; Limit (mathematics); Global temperature; Carbon fibers; Climate change; Carbon dioxide; Atmospheric sciences; Natural resource economics; Climatology; Economics; Mathematics; Chemistry; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004235582,0.0004316105,0.0003619187,0.001829782,0.0003344852,0.001861088,0.0005061315,0.0005218223,0.003193626],"category_scores_gemma":[0.01391601,0.0003460765,0.0004802961,0.002644151,0.000418401,0.0026759,0.0009482132,0.0009873789,0.0007251701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008102391,"about_ca_system_score_gemma":0.0006072614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005128495,"about_ca_topic_score_gemma":0.009553951,"domain_scores_codex":[0.998516,0.0004382218,0.0001564506,0.0004314347,0.0003705308,0.0000873627],"domain_scores_gemma":[0.9933465,0.003199894,0.000757258,0.001168718,0.001435221,0.00009253197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001235064,0.0001435045,0.5621722,0.000910434,0.002332654,0.0002560511,0.001555338,0.01732715,0.04385621,0.04804331,0.006173134,0.3159951],"study_design_scores_gemma":[0.00005504725,0.00009982239,0.8063023,0.0005242594,0.0005588779,0.0004156784,0.001449867,0.03387841,0.03777172,0.03206297,0.08672806,0.0001530271],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8967894,0.00927918,0.04842573,0.003627017,0.0007129601,0.00002778728,0.006429364,0.0004274981,0.03428102],"genre_scores_gemma":[0.9875231,0.001267866,0.007582263,0.0002105757,0.00009467544,0.000008565109,0.001805554,0.0001763327,0.001331117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005128495,"threshold_uncertainty_score":0.02240014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530251484083679,"score_gpt":0.232986360663523,"score_spread":0.2176838458226862,"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."}}