{"id":"W1965083124","doi":"10.3390/en4010026","title":"Spatial Variation and Distribution of Urban Energy Consumptions from Cities in China","year":2010,"lang":"en","type":"article","venue":"Energies","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National Natural Science Foundation of China","keywords":"Theil index; Per capita; Geography; Energy consumption; Beijing; Mainland China; Index (typography); China; Distribution (mathematics); Economic geography; Population; Demography","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":[0.0001339949,0.00004538949,0.00008502159,0.00002660525,0.0001145283,0.00002507936,0.00006664308,0.00006974624,0.0001247441],"category_scores_gemma":[0.00005856613,0.00004436806,0.00001845657,0.00008142659,0.0002770026,0.0001808962,0.00001017997,0.00006181997,3.273368e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001106451,"about_ca_system_score_gemma":0.00004927184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1757881,"about_ca_topic_score_gemma":0.1639537,"domain_scores_codex":[0.9995275,0.0000407352,0.0001306446,0.0001047296,0.0001085728,0.00008781868],"domain_scores_gemma":[0.9997588,0.00006350873,0.00005186174,0.00007427527,0.0000254447,0.0000260726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009151834,0.00003093753,0.9020585,0.000002825273,0.000004118464,3.746839e-7,0.006540483,0.00001304131,0.002259564,0.08742873,0.00003781827,0.001614494],"study_design_scores_gemma":[0.0001177397,0.000004472558,0.9856063,0.000005271685,0.000006304447,1.322123e-8,0.0003189509,0.00005681887,0.0009973687,0.01198465,0.0008518353,0.00005031612],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978696,0.00007410739,0.0004977084,0.0001481727,0.0002395611,0.00002592769,0.00008368165,0.00002292161,0.001038379],"genre_scores_gemma":[0.9994839,0.00004514259,0.00007967201,0.000005702339,0.0001331943,0.000005265335,0.0001056645,0.000002087056,0.0001393503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0835478,"threshold_uncertainty_score":0.8513019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007885585612361828,"score_gpt":0.2424238253156471,"score_spread":0.2345382397032853,"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."}}