{"id":"W2944310230","doi":"10.1371/journal.pone.0215397","title":"Oil price shocks, economic policy uncertainty and industrial economic growth in China","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Granger causality; Economics; China; Oil price; Vector autoregression; Econometrics; Causality (physics); Macroeconomics; Monetary economics; Geography","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":[0.0008423421,0.0003399997,0.0003694283,0.001226305,0.0003251409,0.00106647,0.0002205799,0.0002961488,0.0007842675],"category_scores_gemma":[0.002077346,0.000177856,0.0004714475,0.001899563,0.0003846868,0.0007995867,0.0006870345,0.0004494881,0.00007067248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011008,"about_ca_system_score_gemma":0.001418129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03881097,"about_ca_topic_score_gemma":0.02518175,"domain_scores_codex":[0.9997899,0.00003450465,0.00002030406,0.00004363153,0.00005309427,0.00005874121],"domain_scores_gemma":[0.999078,0.0002818307,0.0003728688,0.00005478579,0.0001269984,0.00008542991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001204187,0.0000611307,0.9387579,0.0000421361,0.0001857404,0.0005550989,0.000239706,0.03923548,0.0007471756,0.005791196,0.0007027857,0.01356133],"study_design_scores_gemma":[0.00003127669,0.00006246269,0.8441553,0.00002821548,0.0001531366,0.00009628609,0.0004588342,0.1464117,0.001072453,0.00585869,0.001633685,0.00003802011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980022,0.0001814609,0.0005280631,0.0002586809,0.000007145276,0.000003496166,0.0001927394,0.00001140428,0.0008147149],"genre_scores_gemma":[0.9994048,0.000150553,0.0000608028,0.00001159523,0.000006256354,0.000001671839,0.0001983055,0.000001553254,0.0001644023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03881097,"threshold_uncertainty_score":0.07717013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03126929881968649,"score_gpt":0.2049311790447272,"score_spread":0.1736618802250407,"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."}}