{"id":"W6947421889","doi":"10.3886/e119621v2","title":"Data and Code for: Crisis Management in Canada: Analyzing Default Risk and Liquidity Demand during Financial Stress","year":2007,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Code (set theory); Market liquidity; Risk management; Liquidity risk; Financial crisis; Default risk; Replication (statistics); Crisis management","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001218062,0.000421183,0.0005509873,0.0003553827,0.0002764228,0.0003213149,0.004521045,0.0001802729,0.000002245431],"category_scores_gemma":[0.0004844483,0.0004395534,0.00002247545,0.0004440812,0.00007030045,0.001819403,0.009691645,0.0005370144,5.569967e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000237605,"about_ca_system_score_gemma":0.0002570039,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2111771,"about_ca_topic_score_gemma":0.7599687,"domain_scores_codex":[0.9964874,0.00005411139,0.0005929067,0.001823709,0.000418407,0.0006234569],"domain_scores_gemma":[0.9949807,0.0002319438,0.0004127089,0.004138213,0.00006054306,0.000175918],"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":[0.00003680478,0.00002454788,0.0006399584,0.0004560577,0.00004173072,0.0002514958,0.00001437651,0.000004181718,0.000003878275,0.00001749064,0.9821136,0.01639585],"study_design_scores_gemma":[0.0006538338,0.00004298715,0.003397031,0.0003556279,0.0001618248,0.00002083407,0.00004471145,0.002864226,0.000516154,0.0003792635,0.9908622,0.0007012972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001893484,0.002151057,0.1837504,0.0000582325,0.0001303436,0.0004548705,0.8115138,0.00004633456,0.000001415256],"genre_scores_gemma":[0.001326112,0.02725003,0.04898363,0.0002571365,0.0001681994,0.00002686931,0.9219521,0.00002872927,0.000007204332],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5487916,"threshold_uncertainty_score":0.9998056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905079657520198,"score_gpt":0.3178488762622594,"score_spread":0.2787980796870574,"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."}}