{"id":"W4226326512","doi":"10.3934/ctr.2022005","title":"Drivers of changes in natural resources consumption of Central African countries","year":2022,"lang":"en","type":"article","venue":"Clean Technologies and Recycling","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Per capita; Divisia index; Natural resource; Energy consumption; Population growth; Development economics; Geography; Population; Consumption (sociology); Economics; Energy intensity; Agricultural economics; Economic growth; Demography; Political science; Engineering","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":[0.0003012088,0.0002274464,0.0001545103,0.0009921191,0.0003118511,0.0008228958,0.0001562087,0.0001915777,0.001268618],"category_scores_gemma":[0.000877965,0.0001530721,0.0002469942,0.002249692,0.000352984,0.0004890304,0.000597748,0.0003648445,0.00008585276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008688436,"about_ca_system_score_gemma":0.000588015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02667536,"about_ca_topic_score_gemma":0.03060373,"domain_scores_codex":[0.9998546,0.00003063526,0.00001144739,0.00002383284,0.00001590748,0.00006370364],"domain_scores_gemma":[0.9995701,0.00007497636,0.0002231351,0.00002199939,0.00005943825,0.00005033166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000580104,0.00002190523,0.9837104,0.00009997829,0.00008336054,0.0005949197,0.001462296,0.0009095356,0.001333749,0.001221367,0.0004343959,0.01007008],"study_design_scores_gemma":[0.000001260629,0.000009538371,0.9959993,0.00003191527,0.00001295622,0.00007705892,0.001576366,0.0003864612,0.0001909221,0.00008080699,0.00162796,0.00000540003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998187,0.0004535586,0.00005961571,0.0001361059,0.000004483151,0.000005462286,0.0004212364,0.000003012395,0.0007294719],"genre_scores_gemma":[0.9993174,0.00027819,0.00007063334,0.0000154598,0.000003573754,0.000004546151,0.0001665039,0.000001461777,0.0001422912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02667536,"threshold_uncertainty_score":0.05304015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768854428421074,"score_gpt":0.1934339790959814,"score_spread":0.1757454348117707,"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."}}