{"id":"W4281259700","doi":"10.1016/j.renene.2022.05.095","title":"Renewable energy and CO2 emissions: New evidence with the panel threshold model","year":2022,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":247,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Per capita; Renewable energy; Economics; Panel data; Energy consumption; Consumption (sociology); Per capita income; Greenhouse gas; Natural resource economics; Gross domestic product; Econometrics; Macroeconomics; Engineering; Population","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005813234,0.0003710569,0.0005459397,0.0002121752,0.0007309024,0.000136125,0.0007735131,0.0001117829,0.0009632267],"category_scores_gemma":[0.00004328563,0.0003428511,0.0001052718,0.0003786307,0.0001438136,0.0004275101,0.0006277708,0.0001741157,0.00001166632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003562137,"about_ca_system_score_gemma":0.000154983,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05686327,"about_ca_topic_score_gemma":0.00395513,"domain_scores_codex":[0.9975333,0.00005029413,0.0006205453,0.001014824,0.0001352664,0.0006458355],"domain_scores_gemma":[0.9979566,0.0001581843,0.0005097811,0.001070167,0.00001220967,0.0002930541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004964587,0.00005377366,0.00184472,0.000007543225,0.00006748123,0.000007314713,0.0001318217,0.8945323,0.0003734774,0.05685074,0.04590752,0.0001736279],"study_design_scores_gemma":[0.001178268,0.0002781436,0.0002698424,0.00004802459,0.00003809818,0.00006416154,0.0004004736,0.3016939,0.002480831,0.1059184,0.5866644,0.0009655118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2021219,0.1275712,0.3019572,0.02054911,0.001502648,0.0007941753,0.0004632734,0.0006442065,0.3443963],"genre_scores_gemma":[0.8370529,0.004427148,0.001052447,0.00240019,0.0001744764,0.0002249316,0.00003239789,0.0001020175,0.1545334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6349311,"threshold_uncertainty_score":0.9999501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04673725833008193,"score_gpt":0.2033263049453668,"score_spread":0.1565890466152849,"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."}}