{"id":"W3100915850","doi":"10.28924/2291-8639-18-2020-981","title":"How Globalization Is Related to Energy Productivity? (A Mathematical Analysis on Iran’s Agricultural Data)","year":2020,"lang":"en","type":"article","venue":"International Journal of Analysis and Applications","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Globalization; Productivity; Agriculture; Cointegration; Context (archaeology); Economics; Shock (circulatory); Causality (physics); Agricultural productivity; Economic globalization; Error correction model; Macroeconomics; Econometrics; Development economics; Classical economics; Geography; Market economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001195556,0.0002127104,0.0003044298,0.002486483,0.0002473711,0.0008019258,0.0004445632,0.0002462577,0.01259187],"category_scores_gemma":[0.005187109,0.0001103106,0.0009366393,0.004731871,0.0003262706,0.0008732287,0.0003961488,0.0006707889,0.001895706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007540765,"about_ca_system_score_gemma":0.000800002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01731687,"about_ca_topic_score_gemma":0.00978981,"domain_scores_codex":[0.9996738,0.00006459138,0.00003587616,0.00005941262,0.000108687,0.0000575742],"domain_scores_gemma":[0.9972951,0.001753361,0.0004116897,0.0001786179,0.0003224992,0.00003867642],"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":[0.0002573025,0.0002086867,0.6530691,0.0004447688,0.0002578611,0.0007533219,0.0006598184,0.03448936,0.00103581,0.03863372,0.05052141,0.219669],"study_design_scores_gemma":[0.00005107829,0.0002668817,0.7996123,0.0001941404,0.0001670648,0.0008708914,0.001883565,0.09344902,0.001854207,0.02197558,0.0796058,0.00006940158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9038882,0.002956839,0.02329787,0.003773428,0.0002064965,0.0001439652,0.04184017,0.0004272108,0.02346589],"genre_scores_gemma":[0.9654008,0.001933233,0.007002773,0.0001138349,0.000100015,0.0001188614,0.01920687,0.00003528506,0.006088276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01731687,"threshold_uncertainty_score":0.04212397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02658846938947264,"score_gpt":0.2384751871096789,"score_spread":0.2118867177202063,"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."}}