{"id":"W2835743335","doi":"10.3390/jrfm11030038","title":"Greenhouse Emissions and Productivity Growth","year":2018,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Total factor productivity; Greenhouse gas; Economics; Econometrics; Productivity; Growth rate; Elasticity (physics); Environmental science; Natural resource economics; Macroeconomics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003421569,0.0004078569,0.0002158051,0.0009546953,0.0001744901,0.0008002395,0.0001294984,0.0003197119,0.001910608],"category_scores_gemma":[0.002549404,0.00009596111,0.0004807385,0.001619373,0.0004579441,0.0005559571,0.0005476317,0.000494299,0.0003219542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007360507,"about_ca_system_score_gemma":0.0004775691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01317976,"about_ca_topic_score_gemma":0.009076898,"domain_scores_codex":[0.9997975,0.00003847958,0.00001106885,0.00003821124,0.00005327901,0.00006141412],"domain_scores_gemma":[0.9982293,0.0007688691,0.0006602156,0.00008862039,0.0001631825,0.00008981564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001462996,0.00007254654,0.8955554,0.0002014565,0.000496065,0.000551304,0.0003868557,0.04911437,0.002005669,0.01523678,0.001760184,0.03447303],"study_design_scores_gemma":[0.000009589917,0.00009363395,0.9630286,0.00005173917,0.0000908581,0.0002197287,0.0004489229,0.008440508,0.001850483,0.01347047,0.01226806,0.00002743293],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626384,0.005508038,0.004478307,0.001852473,0.00005399458,0.00001969298,0.003213706,0.00008359351,0.02215171],"genre_scores_gemma":[0.9948575,0.002197315,0.0002948767,0.00007083111,0.00005088416,0.000007444059,0.000862424,0.000005448923,0.001653258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01317976,"threshold_uncertainty_score":0.02620608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163409076868421,"score_gpt":0.18799443701581,"score_spread":0.1763603462471258,"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."}}