{"id":"W2916961622","doi":"10.5194/essd-8-605-2016","title":"Global Carbon Budget 2016","year":2016,"lang":"en","type":"article","venue":"Earth system science data","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1131,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Oceanic and Atmospheric Administration; Natural Environment Research Council; Sight Research UK","keywords":"Environmental science; Biosphere; Carbon cycle; Carbon sink; Climatology; Climate change; Global change; Deforestation (computer science); Global warming; Atmospheric sciences; Greenhouse gas; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007883668,0.0001568437,0.000137535,0.000006043115,0.0002160556,0.00005191584,0.002061567,0.00004521725,0.0003562843],"category_scores_gemma":[0.00004496783,0.00009731019,0.00002121622,0.0004986248,0.001235423,0.0009168934,0.002034793,0.00003468203,0.001511765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004095228,"about_ca_system_score_gemma":0.00004531401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008513249,"about_ca_topic_score_gemma":0.0001031305,"domain_scores_codex":[0.9975951,0.00003544805,0.0002206138,0.0008192328,0.0007946545,0.0005349063],"domain_scores_gemma":[0.9980028,0.00001890019,0.0000932222,0.001626178,0.000003723879,0.0002551432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002271752,0.00008681351,0.8714116,0.00001565009,0.00001122339,0.00004984467,0.00009831739,0.001796482,0.01237066,0.0009731538,0.00448061,0.1086829],"study_design_scores_gemma":[0.0009596757,0.0001532397,0.8618436,0.0001888052,0.00003041193,0.0002172552,0.000664902,0.06314023,0.0003502537,0.0001386191,0.07136586,0.00094715],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.924835,0.00004761779,0.01566688,0.0003295461,0.0007656564,0.0002920788,0.0001968574,0.0001645567,0.05770182],"genre_scores_gemma":[0.9923303,0.00001376354,0.005737751,0.00006951293,0.00005093943,0.000004404907,0.000006460896,0.000008059222,0.00177877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1077357,"threshold_uncertainty_score":0.9992657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020139291604852,"score_gpt":0.2185320096562698,"score_spread":0.2083306167402213,"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."}}