{"id":"W3134475528","doi":"","title":"Local Air Pollution and Local Stock Returns: Firm Level Evidence from China","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Air pollution; Stock (firearms); Pollution; Beijing; China; Environmental science; Business; Natural resource economics; 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":[0.0008883477,0.0003558211,0.0004148032,0.00127084,0.0005591471,0.0009746337,0.0003907046,0.0004410498,0.001960794],"category_scores_gemma":[0.001543199,0.000175932,0.0007526662,0.001983868,0.0004685772,0.0005344147,0.0008920647,0.000479488,0.0002579722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006326601,"about_ca_system_score_gemma":0.0007018406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08347186,"about_ca_topic_score_gemma":0.1142707,"domain_scores_codex":[0.9995825,0.00007157235,0.00004322517,0.0001039511,0.0001155368,0.00008316977],"domain_scores_gemma":[0.9963199,0.0006737667,0.001688185,0.0002689437,0.0005174261,0.0005317583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002536855,0.00004668586,0.9972017,0.00001941749,0.000143005,0.0001284081,0.0001462951,0.000201852,0.0001816102,0.00006840808,0.0001281571,0.001709103],"study_design_scores_gemma":[0.00000245704,0.00002536081,0.9990854,0.000004398877,0.00005340099,0.00001741172,0.0001843658,0.0003926536,0.00006387696,0.00002564476,0.0001415379,0.000003513247],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987073,0.0002507572,0.00007058672,0.00009785323,0.000004580879,0.000005376161,0.0002931296,0.000002516733,0.0005679844],"genre_scores_gemma":[0.9992488,0.0001366156,0.00003060001,0.00002479284,0.00001150935,0.000002835591,0.0003413282,6.939722e-7,0.0002027149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08347186,"threshold_uncertainty_score":0.165972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02314858742714188,"score_gpt":0.2256273201255702,"score_spread":0.2024787326984283,"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."}}