{"id":"W3127249494","doi":"10.5430/rwe.v12n2p228","title":"Chinese and Indian Stock Markets: Linkages and Interdependencies","year":2021,"lang":"en","type":"article","venue":"Research in World Economy","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantile; Economics; Econometrics; Recession; Quantile regression; Interdependence; Stock (firearms); Ordinary least squares; Robustness (evolution); Stock market; China; Monetary economics; Emerging markets; Financial economics; Macroeconomics; Geography","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":[0.0003706708,0.0001954064,0.0002921013,0.002928122,0.0004243408,0.001527115,0.0003618952,0.0001904816,0.00367468],"category_scores_gemma":[0.00185643,0.0001865083,0.0005491106,0.004933074,0.0004935295,0.0008582069,0.001025296,0.00042308,0.0002880616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008853298,"about_ca_system_score_gemma":0.000862374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07193241,"about_ca_topic_score_gemma":0.07064293,"domain_scores_codex":[0.9997103,0.00003840291,0.00002232027,0.00006271234,0.00007900209,0.00008724609],"domain_scores_gemma":[0.9984113,0.0003325898,0.0007464519,0.00009676092,0.0002711629,0.0001416503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008596499,0.00003596255,0.9663094,0.00006290161,0.0003220622,0.0004915702,0.0008632536,0.002274841,0.0009862108,0.007371891,0.001266506,0.01992953],"study_design_scores_gemma":[0.000003232496,0.0000124679,0.9941103,0.00001174868,0.00008768666,0.00008161845,0.0004362435,0.002748095,0.0001845339,0.0009648915,0.001347303,0.00001193393],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905309,0.0005822117,0.0003779476,0.0004541283,0.000008546677,0.00001106177,0.0006313239,0.0000288871,0.007375067],"genre_scores_gemma":[0.9983169,0.0003152698,0.00008592365,0.00003658374,0.00001132721,0.000004378958,0.0003877304,0.000004368126,0.0008376215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07193241,"threshold_uncertainty_score":0.1430274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05056136142629651,"score_gpt":0.3204968822660746,"score_spread":0.2699355208397781,"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."}}