{"id":"W4391969647","doi":"10.3389/fevo.2024.1338742","title":"China contributed to low-carbon development: carbon emission increased but carbon intensity decreased","year":2024,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Ministry of Land, Infrastructure and Transport","keywords":"Carbon fibers; Environmental science; Carbon cycle; Emission intensity; Intensity (physics); Greenhouse gas; China; Ecology; Chemistry; Materials science; Ecosystem; Geography; Biology; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0007112865,0.0002259304,0.0002977289,0.000156978,0.0001287733,0.00002213546,0.0001245364,0.0002738653,0.00003395042],"category_scores_gemma":[0.0002946575,0.00021886,0.00003618996,0.0003391952,0.000246466,0.0001205005,0.0002169757,0.0002955162,0.000006889495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002530018,"about_ca_system_score_gemma":0.00006743742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003480314,"about_ca_topic_score_gemma":0.000583021,"domain_scores_codex":[0.9982839,0.0001546071,0.0003029304,0.0005323186,0.0002133331,0.0005129446],"domain_scores_gemma":[0.9994582,0.00002905326,0.00004174713,0.0001892648,0.00000957819,0.0002721623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002810741,0.000109812,0.9927265,0.00003022273,0.00001852447,0.00004565235,0.0006902082,0.0001033862,0.003859603,0.000004703779,0.000397968,0.001732333],"study_design_scores_gemma":[0.0004955504,0.0001052406,0.9629405,0.00003951698,0.00002284294,0.00001136408,0.0003884554,0.03244191,0.002015506,0.000937324,0.0003554615,0.0002463991],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961865,0.0002748506,0.0002197996,0.0004536826,0.0007072841,0.0004936644,0.000004867926,0.00008066235,0.001578671],"genre_scores_gemma":[0.9987015,0.00001869319,0.0006132287,0.0001092236,0.00003100519,0.00004343054,0.0000313203,0.00001527103,0.0004363329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03233852,"threshold_uncertainty_score":0.8924852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002621581921800619,"score_gpt":0.1925994484466273,"score_spread":0.1899778665248266,"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."}}