{"id":"W4412908158","doi":"10.1016/j.cnt.2025.100005","title":"Impact of land cover spatial patterns on urban CO₂ emissions: Evidence from China","year":2025,"lang":"en","type":"article","venue":"Carbon Neutral Technologies","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Environment Research Council; National Key Research and Development Program of China; Engineering and Physical Sciences Research Council; National Natural Science Foundation of China; Arts and Humanities Research Council; UK Research and Innovation","keywords":"China; Cover (algebra); Land cover; Environmental science; Geography; Land use; Physical geography; Ecology; Engineering; Archaeology","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":[0.0001036904,0.0001758476,0.0004844936,0.0003662989,0.00004314817,0.00003518615,0.0004661496,0.0002076377,0.0001337773],"category_scores_gemma":[0.0004184968,0.0001517328,0.000217731,0.0003508788,0.00008793786,0.00009327933,0.0001399162,0.0002193069,0.00002362992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007855686,"about_ca_system_score_gemma":0.00002396816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02904556,"about_ca_topic_score_gemma":0.0002395283,"domain_scores_codex":[0.9989022,0.00001152688,0.0004509977,0.0003918284,0.00003355229,0.0002099059],"domain_scores_gemma":[0.9989558,0.0001268526,0.000251134,0.00062202,0.00001840704,0.00002574146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004614493,0.00005159112,0.9947605,0.00001611505,0.0001269774,0.000004158519,0.00005442162,0.0002705498,0.0003254319,0.001053525,0.0005183324,0.002772318],"study_design_scores_gemma":[0.0003048032,0.0002175756,0.9780018,0.0002388538,0.00003181693,2.878655e-7,0.00004056867,0.003421142,0.007528792,0.009696901,0.0003020715,0.0002153522],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994055,0.002038535,0.0004287702,0.000578607,0.0001765269,0.0001189627,0.0009470042,0.0001676841,0.001488858],"genre_scores_gemma":[0.9985487,0.001125712,0.00003799934,0.00002136507,0.0000314969,0.00001557171,0.00005187966,0.000008618136,0.0001586678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02880603,"threshold_uncertainty_score":0.9774201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157063420006229,"score_gpt":0.2622749999550234,"score_spread":0.2307043657549611,"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."}}