{"id":"W4293863418","doi":"10.1109/siu55565.2022.9864678","title":"Call Intent Estimation from ATM Transactions","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Computer science; Demographics; Work (physics); Estimation; Center (category theory); Process (computing); Database transaction; Database; Operating system; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004055127,0.0001986943,0.000210531,0.0002155904,0.002935378,0.0004776879,0.001031956,0.00005598474,0.001163716],"category_scores_gemma":[0.000008467491,0.0002245733,0.0000638802,0.0009573055,0.0001992211,0.0007237116,0.0004246699,0.0005509258,0.00009315941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007378735,"about_ca_system_score_gemma":0.0001317578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002053251,"about_ca_topic_score_gemma":0.0004967535,"domain_scores_codex":[0.9985495,0.00006655165,0.0004363383,0.0004019378,0.0003176272,0.0002280165],"domain_scores_gemma":[0.9983656,0.0001132628,0.0003099866,0.000895814,0.0002801297,0.00003519951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004668269,0.0008534958,0.0007715666,0.0002004905,0.00006609455,7.671547e-7,0.001602325,0.002179095,0.00101805,0.0671944,0.0009350858,0.9251319],"study_design_scores_gemma":[0.0004948643,0.00001899029,0.001655442,0.00004902192,0.0002115768,0.000005616631,0.006933331,0.6826303,0.00002625574,0.02469478,0.2827812,0.0004986628],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0249497,0.003731956,0.9251816,0.02460557,0.0001099071,0.001571351,0.000245048,0.0008372411,0.01876764],"genre_scores_gemma":[0.991414,0.00009118408,0.003466495,0.001693128,0.0000894014,0.001982054,0.0008063681,0.00002527013,0.0004320596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9664643,"threshold_uncertainty_score":0.9997494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04352596920783505,"score_gpt":0.2713523413911345,"score_spread":0.2278263721832995,"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."}}