{"id":"W3142029566","doi":"10.2139/ssrn.3581603","title":"Is There Anybody Out There? Detecting Operational Outages from LVTS Transaction Data","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of Canada","funders":"","keywords":"Database transaction; Transaction data; Computer science; Business; Database; 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":[0.001795124,0.0003018916,0.0004769826,0.002934583,0.0002022609,0.001251071,0.0006056527,0.0008003867,0.001191215],"category_scores_gemma":[0.01150571,0.0002240072,0.0002380326,0.002233968,0.0002371143,0.001686137,0.000813164,0.0009331427,0.0009278919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002867529,"about_ca_system_score_gemma":0.0003742549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004050101,"about_ca_topic_score_gemma":0.005304996,"domain_scores_codex":[0.998928,0.0002518658,0.000147096,0.000166096,0.0003625111,0.0001444908],"domain_scores_gemma":[0.9896787,0.004646181,0.002973252,0.0008825739,0.00125611,0.0005630922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002833066,0.0001146291,0.91303,0.00008922112,0.0001015801,0.0004918276,0.0004557969,0.005757086,0.003776153,0.0009036048,0.008316637,0.06668022],"study_design_scores_gemma":[0.00005091215,0.0003165354,0.8209689,0.0001929073,0.0001541236,0.0008097777,0.003667627,0.1487442,0.004808869,0.006310048,0.0139129,0.00006315878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781893,0.0004160871,0.01017409,0.001075837,0.00008406613,0.00004430675,0.007108368,0.0004234525,0.002484492],"genre_scores_gemma":[0.9913111,0.0001631561,0.0027276,0.0000773459,0.0001091122,0.00001560925,0.005012604,0.00002102065,0.000562496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004050101,"threshold_uncertainty_score":0.009493649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05834592724319394,"score_gpt":0.2570937329798832,"score_spread":0.1987478057366893,"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."}}