{"id":"W1941612930","doi":"10.5430/jms.v6n3p21","title":"An Empirical Study of Alxa League Energy Consumption and Environmental Pollution in China","year":2015,"lang":"en","type":"article","venue":"Journal of Management and Strategy","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy consumption; China; Environmental pollution; Consumption (sociology); Pollution; Natural resource economics; League; Environmental science; Business; Environmental economics; Environmental planning; Environmental protection; Economics; Geography; Engineering; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008535088,0.00022923,0.0002397952,0.001197771,0.001093284,0.001201403,0.0007052876,0.0004198952,0.001895615],"category_scores_gemma":[0.002030992,0.00017148,0.0003850346,0.002160355,0.0008971954,0.0008899863,0.00101476,0.0006186969,0.0001776033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003097683,"about_ca_system_score_gemma":0.001697231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1590321,"about_ca_topic_score_gemma":0.2059826,"domain_scores_codex":[0.9993956,0.000145466,0.00003953452,0.00008827872,0.0001401152,0.0001909544],"domain_scores_gemma":[0.9973356,0.0006451092,0.0007738546,0.0001597932,0.0003876553,0.0006979057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002564952,0.0001362971,0.9949937,0.000008926309,0.00003055677,0.0001866074,0.002244411,0.0002281933,0.0001067947,0.000377945,0.0002754001,0.001385474],"study_design_scores_gemma":[0.000004097142,0.00005064284,0.9906845,0.000006380526,0.000009145321,0.00002171478,0.00718294,0.001424385,0.00005431247,0.00004906924,0.0005073259,0.000005546188],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994056,0.00002106342,0.00001427914,0.00006092852,0.000001002113,0.000003649716,0.00004031483,0.000001132957,0.0004521674],"genre_scores_gemma":[0.9994627,0.00003090243,0.00001762125,0.00001528396,0.000001850639,0.000004448734,0.0001152058,6.58472e-7,0.0003512007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1590321,"threshold_uncertainty_score":0.3162129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03028262308525885,"score_gpt":0.2531327157986539,"score_spread":0.222850092713395,"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."}}