{"id":"W4318049483","doi":"10.3390/su15032218","title":"The Nexus between GHGs Emissions and Clean Growth: Empirical Evidence from Canadian Provinces","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; Dalhousie University","funders":"","keywords":"Greenhouse gas; Estimator; Energy intensity; Econometrics; Panel data; Nexus (standard); Emission intensity; Economics; Environmental science; Kuznets curve; Efficient energy use; Natural resource economics; Geography; Statistics; Energy (signal processing); Mathematics; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001405696,0.0003987981,0.0006750369,0.002899024,0.002575827,0.001980831,0.001287161,0.0003967926,0.002936429],"category_scores_gemma":[0.006121739,0.0003537821,0.001243456,0.009602062,0.001111454,0.0005766277,0.001077445,0.0007951084,0.0002485366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03078353,"about_ca_system_score_gemma":0.06454071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9979312,"about_ca_topic_score_gemma":0.9985682,"domain_scores_codex":[0.9985039,0.000117814,0.000105717,0.0002317956,0.0005525232,0.000488295],"domain_scores_gemma":[0.9892731,0.001674151,0.001292448,0.0004841252,0.006221513,0.001054652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001928303,0.00005738167,0.971667,0.0002894362,0.0004234557,0.0004180921,0.001671308,0.001903828,0.0002680669,0.002639841,0.006571063,0.01389777],"study_design_scores_gemma":[0.00001420171,0.0000170786,0.9851009,0.0001475791,0.0002430308,0.00005652061,0.00340018,0.001473467,0.0002283092,0.000170395,0.009104899,0.00004336761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547471,0.006106565,0.0005357855,0.002365356,0.00005128921,0.00004223803,0.02022566,0.00004650093,0.01587941],"genre_scores_gemma":[0.9876687,0.002275022,0.0003690725,0.0001738397,0.000008834944,0.00001121491,0.007181054,0.00001515589,0.002297041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03078353,"threshold_uncertainty_score":0.2233512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763301132171678,"score_gpt":0.2994653465557933,"score_spread":0.2718323352340765,"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."}}