{"id":"W4407418359","doi":"10.1002/ldr.5458","title":"Exploring the Role of Land Utilization, Renewable Energy, and <scp>ICT</scp> to Counter the Environmental Emission: A Panel Study of Selected <scp>G20</scp> and <scp>OECD</scp> Countries","year":2025,"lang":"en","type":"article","venue":"Land Degradation and Development","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Renewable energy; Business; Information and Communications Technology; Natural resource economics; Panel data; Greenhouse gas; Environmental economics; Economics; Engineering; Political science; Electrical engineering; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008905428,0.0002040272,0.0002714912,0.0006240794,0.0004103945,0.0007706181,0.0002856824,0.0004851708,0.002384436],"category_scores_gemma":[0.001187641,0.0001434783,0.0007159857,0.0012542,0.0002709525,0.0003844194,0.0007054457,0.0005419008,0.0003590759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004606656,"about_ca_system_score_gemma":0.0004480486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03124388,"about_ca_topic_score_gemma":0.03493521,"domain_scores_codex":[0.999638,0.0001794781,0.00001320897,0.00005314542,0.00003036096,0.00008575915],"domain_scores_gemma":[0.9986505,0.0006191174,0.0003292899,0.0001057802,0.0001352783,0.0001601445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000104912,0.0002385361,0.9845776,0.00002797575,0.0003981485,0.0002648844,0.0003119333,0.00617107,0.0003382092,0.0007103416,0.002040142,0.004816169],"study_design_scores_gemma":[0.0000111205,0.0001223954,0.9877663,0.0000288927,0.0001644758,0.00006944012,0.00228007,0.006055875,0.0004300533,0.0004171592,0.002638711,0.00001572369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967626,0.0001463446,0.0003176205,0.0001648387,0.000003832816,0.000008199,0.001669851,0.000002928167,0.0009237595],"genre_scores_gemma":[0.9970962,0.0001005271,0.0001397044,0.00003918606,0.000005087718,0.00001006193,0.002199791,0.000001808611,0.0004077411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03124388,"threshold_uncertainty_score":0.06212407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03609232090620467,"score_gpt":0.1992313619066227,"score_spread":0.163139041000418,"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."}}