{"id":"W6969175680","doi":"10.5683/sp3/ycewnz","title":"Replication Data and Code for: The life cycle of trading activity and liquidity of Government of Canada bonds: Evidence from cash, repo and securities lending markets","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Market liquidity; Replication (statistics); Government (linguistics); Replicate; Code (set theory)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001714951,0.002275782,0.001645555,0.005041808,0.002383817,0.004328426,0.004357443,0.001978012,0.1051658],"category_scores_gemma":[0.0158046,0.001292446,0.001808648,0.0100514,0.0008655277,0.001317384,0.002226229,0.002395151,0.05780242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01026679,"about_ca_system_score_gemma":0.0208023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8637374,"about_ca_topic_score_gemma":0.9100979,"domain_scores_codex":[0.9984787,0.0001299311,0.0001281478,0.0003373837,0.0005155001,0.0004102285],"domain_scores_gemma":[0.9901313,0.001200234,0.0006934172,0.001924813,0.005076324,0.0009739367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004898788,0.00001276711,0.001358142,0.0001985507,0.00002737169,0.00001101192,0.00002941175,0.0002329533,0.00003357592,0.0003451392,0.9966366,0.001065473],"study_design_scores_gemma":[0.00063125,0.00001606531,0.02303158,0.0003948854,0.00007847918,0.00004772913,0.0002122702,0.0007577669,0.0004081802,0.001100303,0.9732279,0.00009357164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000089971,0.00001996321,0.00002290418,0.00003879148,0.00001296404,0.000009812345,0.9993305,0.0001494287,0.0003256407],"genre_scores_gemma":[0.0006868299,0.00002764074,0.0001797877,0.00002842906,0.000006519935,0.0000795719,0.998007,0.00008187253,0.0009023909],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1362626,"threshold_uncertainty_score":0.3518145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06062385007036381,"score_gpt":0.2978106075916171,"score_spread":0.2371867575212533,"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."}}