{"id":"W7051746549","doi":"","title":"Oil Prices and Stock Markets: An Empirical Analysis From Russia, Canada, USA and Japan","year":2019,"lang":"en","type":"article","venue":"AYBU AVESIS","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Stock (firearms); Oil price; Stock market; Empirical research; Volatility (finance)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002706169,0.0002567478,0.0003617425,0.00140586,0.001324588,0.001293605,0.0003944246,0.0003098217,0.001034579],"category_scores_gemma":[0.001340026,0.0001844118,0.0005567272,0.004304087,0.0005463931,0.0004199973,0.0005355194,0.0005249582,0.0001499415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004119263,"about_ca_system_score_gemma":0.006857942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9217292,"about_ca_topic_score_gemma":0.9455121,"domain_scores_codex":[0.999792,0.00001158637,0.000009484693,0.00002608834,0.00007025946,0.00009047988],"domain_scores_gemma":[0.9985754,0.0002354479,0.0002680589,0.00003790479,0.000564247,0.0003188138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001471031,0.00005525253,0.9925702,0.00002276751,0.0001407594,0.000303355,0.0007512277,0.0005393333,0.0003345454,0.0004008267,0.001167033,0.00356762],"study_design_scores_gemma":[0.000005810169,0.00001120344,0.9965041,0.000008369078,0.00008889754,0.00004493656,0.001630716,0.0006433044,0.0001275516,0.00003113225,0.0008947566,0.000009293429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979779,0.0002108263,0.00002991847,0.00008722549,0.000002346173,0.000003167954,0.0007643861,0.000002513245,0.0009216314],"genre_scores_gemma":[0.9965097,0.0004600853,0.00005291009,0.00002808019,0.000005716824,0.00000304965,0.001999217,0.000003352038,0.0009378225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07827079,"threshold_uncertainty_score":0.1574634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008907351699501475,"score_gpt":0.2564154952951918,"score_spread":0.2475081435956903,"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."}}