{"id":"W2759082369","doi":"10.5267/j.ac.2017.9.001","title":"A framework for evaluating the performance of automated teller machine in banking industries: A queuing model-cum-TOPSIS approach","year":2017,"lang":"en","type":"article","venue":"Accounting","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"TOPSIS; Queueing theory; Computer science; Operations research; Industrial engineering; Engineering; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002266967,0.0002644542,0.0003544507,0.0002300924,0.001236922,0.0008821211,0.001300403,0.0001971422,0.00002822556],"category_scores_gemma":[0.002529631,0.0002052074,0.00007979104,0.0005337645,0.0001653595,0.002866022,0.0006356374,0.0004244655,0.000009192248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003138433,"about_ca_system_score_gemma":0.00009442327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001638042,"about_ca_topic_score_gemma":0.00005286612,"domain_scores_codex":[0.9980571,0.00001209277,0.0006031239,0.0004268949,0.0004030664,0.000497687],"domain_scores_gemma":[0.9975483,0.0002348012,0.001020393,0.0008240648,0.0003647399,0.000007667243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004328151,0.0004044837,0.6279584,0.003380954,0.0001632158,0.00000303978,0.001460269,0.1204157,0.002554435,0.07406195,0.001121802,0.1680429],"study_design_scores_gemma":[0.0003248556,0.000007484678,0.009242116,0.0006210635,0.0000455415,0.000001482157,0.0003183291,0.9860032,0.0002920783,0.002473903,0.0004102883,0.0002596999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705637,0.0001241486,0.02417547,0.0006287051,0.0002663433,0.000611276,0.000006923937,0.000162754,0.003460664],"genre_scores_gemma":[0.9891099,0.0000118256,0.009825666,0.0003624414,0.0004567838,0.0001063256,0.0000312886,0.00004657235,0.00004917301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8655874,"threshold_uncertainty_score":0.9513531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1609270817145941,"score_gpt":0.3681744149478025,"score_spread":0.2072473332332085,"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."}}