{"id":"W2141028856","doi":"10.1111/j.1538-4616.2011.00440.x","title":"Information and Liquidity","year":2011,"lang":"en","type":"article","venue":"Journal of money credit and banking","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Business Development Bank of Canada","funders":"","keywords":"Market liquidity; Currency; Private information retrieval; Economics; Monetary economics; Value (mathematics); Bond; Financial economics; Stock (firearms); Construct (python library); Microeconomics; Business; Econometrics; Finance; Computer science; Computer security","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":[0.001692748,0.0004672993,0.000676939,0.001055494,0.0009285645,0.004392929,0.0007370661,0.002202385,0.01603347],"category_scores_gemma":[0.02477611,0.0002895407,0.000543933,0.001479604,0.002419822,0.007880262,0.001800639,0.002324657,0.0009001305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484479,"about_ca_system_score_gemma":0.0008167887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002220778,"about_ca_topic_score_gemma":0.001116525,"domain_scores_codex":[0.9990357,0.0003200019,0.00004305859,0.0001516254,0.0001738934,0.0002757184],"domain_scores_gemma":[0.9779098,0.01398442,0.005993786,0.0008572766,0.0005828213,0.0006719764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005984409,0.0005161314,0.03009712,0.0003385554,0.0001534937,0.0008427828,0.001763258,0.06177688,0.003117192,0.8506175,0.004990593,0.0451881],"study_design_scores_gemma":[0.0001180282,0.0002775756,0.009956101,0.0001112925,0.00009118161,0.0003453095,0.0006392742,0.0459982,0.001422964,0.934437,0.006513673,0.00008946646],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7844954,0.00538,0.08043274,0.01587905,0.0001814523,0.00009964748,0.0008262213,0.0001902784,0.1125152],"genre_scores_gemma":[0.9943331,0.000627836,0.001155072,0.0002007901,0.00008288494,0.00001606489,0.00006179409,0.00001059079,0.003511835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01603347,"threshold_uncertainty_score":0.05363733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03841745756597517,"score_gpt":0.1931999148550922,"score_spread":0.154782457289117,"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."}}