{"id":"W3186320746","doi":"10.1016/j.oneear.2021.06.005","title":"Meeting well-below 2°C target would increase energy sector jobs globally","year":2021,"lang":"en","type":"article","venue":"One Earth","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Horizon 2020; Kirke-, Utdannings- og Forskningsdepartementet; Norges Forskningsråd; European Commission","keywords":"Fossil fuel; Work (physics); Natural resource economics; Climate change; Renewable energy; Baseline (sea); Business; Greenhouse gas; Job creation; Global warming; Economics; Labour economics; Engineering; Political science; Ecology","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":[0.0005733444,0.0003632881,0.0002154712,0.0004398834,0.0003162306,0.001104115,0.0002618211,0.000565965,0.003332465],"category_scores_gemma":[0.001239153,0.0001845865,0.0008017802,0.001215133,0.0002739668,0.001100552,0.0006647118,0.0006808632,0.0008238468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008979805,"about_ca_system_score_gemma":0.001228002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03740232,"about_ca_topic_score_gemma":0.04118157,"domain_scores_codex":[0.9997039,0.0000777079,0.00001117027,0.00005345224,0.00005786636,0.00009569435],"domain_scores_gemma":[0.9996544,0.00006561321,0.00009435561,0.00003921189,0.00009137858,0.00005502051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003370336,0.0003203456,0.5235372,0.0003352496,0.0003173438,0.0002767357,0.0004650491,0.3543036,0.002300941,0.02886716,0.03169394,0.05724531],"study_design_scores_gemma":[0.0001214993,0.00040122,0.6907071,0.0002358808,0.0001713907,0.0001942889,0.002683969,0.1833604,0.003536629,0.02912895,0.08934475,0.0001139867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9385429,0.0003730192,0.01150564,0.002821977,0.00009298669,0.00006133597,0.02349362,0.0002679306,0.02284058],"genre_scores_gemma":[0.9845855,0.0003076349,0.003796114,0.0002048962,0.00002184259,0.00006698874,0.008799158,0.00002456944,0.002193312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03740232,"threshold_uncertainty_score":0.07436925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05161716047351595,"score_gpt":0.2125746925305622,"score_spread":0.1609575320570463,"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."}}