{"id":"W2969955386","doi":"10.1111/jfir.12191","title":"CORPORATE LIQUIDITY AND NBER RECESSION ANNOUNCEMENTS","year":2019,"lang":"en","type":"article","venue":"The Journal of Financial Research","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recession; Market liquidity; Business cycle; Quarter (Canadian coin); Monetary economics; Monetary policy; Business; Economics; Financial system; Macroeconomics","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":[0.003085773,0.0002292672,0.000345725,0.001595693,0.0004422853,0.001837451,0.0002599196,0.0007148764,0.004600078],"category_scores_gemma":[0.02803957,0.0001581038,0.00016013,0.00174634,0.0003359807,0.0007424066,0.0008860911,0.001326205,0.001080935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043668,"about_ca_system_score_gemma":0.0005007999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01533729,"about_ca_topic_score_gemma":0.01526245,"domain_scores_codex":[0.998963,0.0002353994,0.0001284023,0.0001355588,0.0003635888,0.0001741197],"domain_scores_gemma":[0.952179,0.01354713,0.02908634,0.000837771,0.003281266,0.001068465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001788223,0.0002130047,0.9367556,0.0001562115,0.0001735248,0.0003085183,0.0006562845,0.003350534,0.002079672,0.002685821,0.02457373,0.02725882],"study_design_scores_gemma":[0.00008837288,0.0001914164,0.9797823,0.0001085145,0.00009072702,0.0001022022,0.0007542339,0.004250848,0.00180301,0.001053049,0.01173034,0.00004493767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598283,0.002102862,0.0009402464,0.003930565,0.000151083,0.00007680638,0.01025019,0.0001807914,0.02253922],"genre_scores_gemma":[0.9917046,0.000791498,0.0001844652,0.000282343,0.0001732446,0.00003645251,0.004392174,0.00002246637,0.002412771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01533729,"threshold_uncertainty_score":0.030496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1176322912400352,"score_gpt":0.3284591092537756,"score_spread":0.2108268180137405,"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."}}