{"id":"W4242363525","doi":"10.5194/acp-2019-677","title":"Carbon dioxide emissions in Northern China based on atmosphericobservations from 2005 to 2009","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Harvard Global Institute","keywords":"Beijing; Environmental science; China; Greenhouse gas; Climatology; Carbon dioxide; Meteorology; Atmospheric sciences; Geography","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":[0.0004286845,0.0003710413,0.0002180071,0.0008397203,0.0003001172,0.000503686,0.0002557129,0.0001475896,0.0004496683],"category_scores_gemma":[0.0004267329,0.0001365315,0.0004028059,0.001502276,0.0002182523,0.0003356389,0.0002967757,0.0001077804,0.00009208526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001464934,"about_ca_system_score_gemma":0.001039497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1658601,"about_ca_topic_score_gemma":0.2318848,"domain_scores_codex":[0.9998183,0.00002211697,0.00002173998,0.0000669096,0.00004518152,0.00002591065],"domain_scores_gemma":[0.999513,0.00005347691,0.0001470269,0.00006228368,0.0001794632,0.00004475135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008871637,0.00003486085,0.9774526,0.0000557593,0.0001484975,0.0001932206,0.000168849,0.01191554,0.002212236,0.0001554211,0.0004832978,0.007090982],"study_design_scores_gemma":[0.000002964233,0.00001130517,0.9900904,0.000005635488,0.0000329859,0.00002583179,0.00009477466,0.008323461,0.000840332,0.00002794844,0.0005348619,0.000009487101],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997076,0.00008274283,0.000214134,0.00001405603,0.0000028551,0.000003411897,0.001998376,0.00001779423,0.0005906377],"genre_scores_gemma":[0.9960476,0.00007020926,0.0002836133,0.000006647592,0.00000369643,0.000008601279,0.003330095,0.000002029266,0.0002476065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1658601,"threshold_uncertainty_score":0.3297894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007727776984858018,"score_gpt":0.2047639870017287,"score_spread":0.1970362100168706,"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."}}