{"id":"W6907961745","doi":"10.25384/sage.c.6321327.v1","title":"Reduce carbon emissions efficiently: The influencing factors and decoupling relationships of carbon emission from high-energy consumption and high-emission industries in China","year":2022,"lang":"en","type":"other","venue":"Sage Journals Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Divisia index; Greenhouse gas; Decoupling (probability); Emission intensity; Energy intensity; Per capita; Energy consumption; Carbon fibers; Gross domestic product","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":[0.0006066004,0.0005614327,0.0003540313,0.001504797,0.000742659,0.001074945,0.0003524583,0.0002770437,0.001667049],"category_scores_gemma":[0.0009899447,0.0002705202,0.0009141362,0.002040853,0.0006453309,0.0009188075,0.001053844,0.0003927731,0.0001133952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002145087,"about_ca_system_score_gemma":0.003579008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07948434,"about_ca_topic_score_gemma":0.1075423,"domain_scores_codex":[0.9994137,0.00008003356,0.00003773984,0.00009755297,0.0001934958,0.0001773921],"domain_scores_gemma":[0.9995412,0.0001014886,0.000112476,0.00002617619,0.0001242744,0.00009443161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005453942,0.0001007104,0.9565179,0.0001187306,0.0003129321,0.0006062094,0.0008264573,0.01116831,0.002810436,0.005464177,0.0004881965,0.02153154],"study_design_scores_gemma":[0.000006959458,0.00002897703,0.9859952,0.0000266296,0.0001058301,0.0000629378,0.001011372,0.008768409,0.0008144224,0.001840217,0.001317059,0.00002195885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9938896,0.0002234688,0.001069959,0.0003663964,0.000006062822,0.00001866823,0.0001479729,0.00001324464,0.004264634],"genre_scores_gemma":[0.9984067,0.0002304739,0.0002978435,0.00002927915,0.000003958317,0.000008217615,0.0001623163,0.000004321014,0.0008569034],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07948434,"threshold_uncertainty_score":0.1580434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06180656359994581,"score_gpt":0.2986836981520522,"score_spread":0.2368771345521064,"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."}}