{"id":"W3007500643","doi":"10.2139/ssrn.3490600","title":"The Effect of IFRS 9 on the Timeliness of Loan Loss Recognition","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Loan; Business; Credit risk; Accounting; Provisioning; Sample (material); Financial system; Bank credit; Actuarial science; Finance; Telecommunications","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":[0.01646021,0.0002557047,0.0007072449,0.001229221,0.0006505251,0.00390472,0.001515873,0.002881532,0.01055413],"category_scores_gemma":[0.1165234,0.0002820992,0.0007894006,0.001123211,0.001152163,0.001611789,0.001151208,0.003017621,0.001912892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002028374,"about_ca_system_score_gemma":0.00236987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008977747,"about_ca_topic_score_gemma":0.007183956,"domain_scores_codex":[0.9922633,0.00285237,0.0007209226,0.001015146,0.001343807,0.001804292],"domain_scores_gemma":[0.7111431,0.1913961,0.07482708,0.008152941,0.007280854,0.007199849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01744228,0.003075145,0.7018653,0.000329939,0.0006523689,0.001293541,0.001008316,0.09440207,0.007612668,0.02848664,0.01527345,0.1285583],"study_design_scores_gemma":[0.0003821737,0.003895137,0.9270121,0.00008454582,0.0003957694,0.000580345,0.001609246,0.0435182,0.005407087,0.01166205,0.0053199,0.0001333739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790102,0.0005907149,0.001942625,0.003033049,0.0001538412,0.00003621218,0.001090048,0.000224289,0.01391906],"genre_scores_gemma":[0.9982833,0.00004800777,0.0001396427,0.00008354581,0.00005997641,0.000005858652,0.0001903717,0.00001078135,0.001178618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01646021,"threshold_uncertainty_score":0.08705097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008766260112715954,"score_gpt":0.210107587724861,"score_spread":0.2013413276121451,"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."}}