{"id":"W1545542433","doi":"10.3968/j.css.1923669720120804.1222","title":"Analysis of the Impact of Non- Oil Sector on Economic Growth","year":2012,"lang":"en","type":"article","venue":"Canadian social science","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Oil boom; Revenue; Earnings; Agriculture; Boom; Economics; Product (mathematics); Foreign exchange; Exchange rate; Production (economics); Agricultural economics; Economy; Business; Petroleum; Ordinary least squares; Export performance; International trade; Monetary economics; Finance; Macroeconomics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005608904,0.00007733089,0.0002779005,0.0004615426,0.0001739046,0.00002285664,0.0004481956,0.00004762654,0.000555756],"category_scores_gemma":[0.0000501722,0.00006511488,0.0002503918,0.0008504925,0.0002347909,0.0001485754,0.00003656906,0.00006395914,0.00006167282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317021,"about_ca_system_score_gemma":0.0002703146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06520063,"about_ca_topic_score_gemma":0.005415625,"domain_scores_codex":[0.9991146,0.000004613826,0.0002914949,0.0001691367,0.00003181513,0.0003883049],"domain_scores_gemma":[0.9993182,0.00001882601,0.0002648227,0.0001577339,0.00001937786,0.0002209914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002085666,0.000009049561,0.973851,0.000002520828,0.0001082787,4.723034e-8,0.0009933639,0.0000560497,0.00002411048,0.02354314,0.0004012015,0.001009129],"study_design_scores_gemma":[0.00006814198,0.0000106368,0.9969801,0.000002212919,0.00001096609,1.013934e-7,0.00008632787,0.0006057214,0.0001045152,0.0001725254,0.00186273,0.00009604885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8484092,0.00005524212,0.000001269916,0.00008224339,0.0002653358,0.00002944401,0.0002135815,0.000001419337,0.1509422],"genre_scores_gemma":[0.9994755,0.000009612654,0.00001165164,0.00009419076,0.00006841615,0.000002131377,0.000001793917,0.000004516809,0.0003321344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1510663,"threshold_uncertainty_score":0.9410243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01904681885797093,"score_gpt":0.2289910487240884,"score_spread":0.2099442298661175,"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."}}