{"id":"W1967789545","doi":"10.1073/pnas.0805800106","title":"Setting cumulative emissions targets to reduce the risk of dangerous climate change","year":2009,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":335,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Victoria","funders":"Canadian Foundation for Climate and Atmospheric Sciences; Carnegie Mellon University; National Science Foundation","keywords":"Greenhouse gas; Environmental science; Climate change; Range (aeronautics); Atmospheric sciences; Carbon dioxide; Carbon dioxide equivalent; Carbon cycle; Global warming; Climate sensitivity; Global temperature; Climatology; Climate model; Chemistry; Ecology; Engineering; Ecosystem","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":[0.003631826,0.0009211685,0.0004752165,0.001127228,0.0004832045,0.001482865,0.001156045,0.001087123,0.001988738],"category_scores_gemma":[0.01475664,0.0002771497,0.0005763082,0.000667199,0.0006947884,0.001748064,0.001604643,0.001104117,0.0002774402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001299166,"about_ca_system_score_gemma":0.001367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003640211,"about_ca_topic_score_gemma":0.003856281,"domain_scores_codex":[0.9975435,0.0008153942,0.0001109569,0.0003959869,0.0008425072,0.0002916346],"domain_scores_gemma":[0.9917132,0.004326602,0.001999751,0.000815031,0.0009263483,0.0002191019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001958814,0.00008102426,0.02635306,0.0001038361,0.0001437296,0.0001033792,0.0001701812,0.8899276,0.006901685,0.03851959,0.001012659,0.03648737],"study_design_scores_gemma":[0.00006671978,0.0005065539,0.03969447,0.00009422324,0.0002130444,0.0003185003,0.0004295246,0.8358839,0.01989859,0.09197302,0.01079249,0.0001289607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.314388,0.0006673977,0.6655619,0.00110168,0.00009715336,0.0001566554,0.0003915379,0.0007652366,0.01687044],"genre_scores_gemma":[0.9772003,0.0001905753,0.02151405,0.00009093222,0.00002895289,0.00006802531,0.0000972737,0.00005025266,0.0007594658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003640211,"threshold_uncertainty_score":0.01920718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02750290592699955,"score_gpt":0.2889581413659819,"score_spread":0.2614552354389824,"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."}}