{"id":"W2055456146","doi":"10.5539/ibr.v1n4p40","title":"Data Enriched Voice Service Analysis and Forecast","year":2009,"lang":"en","type":"article","venue":"International Business Research","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interoperability; Service (business); Personalization; Computer science; Call centre; Work (physics); Business; Telecommunications; World Wide Web; Marketing; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001263473,0.0006800655,0.0004244909,0.00229222,0.0003657964,0.001801518,0.0005680561,0.0008152463,0.002645326],"category_scores_gemma":[0.005274625,0.0002273659,0.0004015828,0.001669835,0.0002622838,0.002279233,0.0004755482,0.0008116211,0.001296488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001923876,"about_ca_system_score_gemma":0.001019622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01743719,"about_ca_topic_score_gemma":0.00814237,"domain_scores_codex":[0.9990251,0.0001387353,0.00005279856,0.0001562761,0.0005271703,0.0000998861],"domain_scores_gemma":[0.997171,0.001064663,0.000224209,0.0001968076,0.001231819,0.0001115605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001286018,0.0002562842,0.1130824,0.0001937753,0.0001312332,0.000736416,0.0005269065,0.5500023,0.02402703,0.03407051,0.01064775,0.2650394],"study_design_scores_gemma":[0.00001380436,0.00004103952,0.008934788,0.000009981462,0.00002327065,0.00005446568,0.0001637002,0.9760101,0.004963451,0.005118676,0.004633514,0.00003320992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5508625,0.000632859,0.4166224,0.001569889,0.0002658646,0.0002463885,0.006418596,0.003319194,0.02006239],"genre_scores_gemma":[0.9526854,0.000316375,0.03921133,0.00007765259,0.0001025005,0.00007756407,0.003717273,0.0001143055,0.003697571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01743719,"threshold_uncertainty_score":0.03467137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1398868676905564,"score_gpt":0.3984806820133297,"score_spread":0.2585938143227733,"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."}}