{"id":"W4220884181","doi":"10.1371/journal.pone.0265674","title":"Evaluating factors contributing to the failure of information system in the banking industry","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"TOPSIS; Failure mode and effects analysis; Rough set; Computer science; Order (exchange); Key (lock); Field (mathematics); Risk analysis (engineering); Information system; Empirical research; Business; Computer security; Data mining; Finance; Operations research; Reliability engineering; Engineering; Mathematics; Statistics","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":[0.004723287,0.0005967305,0.0007382449,0.006739864,0.0008278831,0.002072661,0.0003239942,0.000630284,0.001337412],"category_scores_gemma":[0.01533992,0.0002083371,0.0007289828,0.005071991,0.0008291882,0.001124651,0.0009397177,0.0005323919,0.0001434434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001911959,"about_ca_system_score_gemma":0.001543469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007820938,"about_ca_topic_score_gemma":0.007029134,"domain_scores_codex":[0.9962913,0.000904242,0.0005077667,0.0002356756,0.001550402,0.0005107087],"domain_scores_gemma":[0.9831322,0.009448023,0.003530169,0.0003589671,0.003046664,0.0004839865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004132882,0.0001798422,0.9161016,0.0004116195,0.0002231367,0.0005469786,0.003231467,0.01241653,0.002647151,0.0009822674,0.0005111751,0.06233493],"study_design_scores_gemma":[0.00001358718,0.0003640195,0.9445791,0.0001574413,0.0002249278,0.0002162829,0.01054302,0.03827552,0.002530749,0.001681335,0.001337005,0.00007695993],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949248,0.0002514675,0.003168182,0.0001008355,0.000006896516,0.0000802571,0.0001484894,0.000009822118,0.001309248],"genre_scores_gemma":[0.9984131,0.0001360049,0.001134323,0.000006886441,0.000003830057,0.00002300977,0.0001255811,0.000001365274,0.0001558691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007820938,"threshold_uncertainty_score":0.02497941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08864077543066802,"score_gpt":0.2869646086909101,"score_spread":0.1983238332602421,"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."}}