{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098292,0.00008377524,0.0001331449,0.0007244704,0.0001124678,0.0005422662,0.002725366,0.00004863041,0.00002786536],"category_scores_gemma":[0.000461033,0.00007409402,0.00002113125,0.00369823,0.0000337907,0.0009579891,0.0009159039,0.0001450038,0.0001372436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004552468,"about_ca_system_score_gemma":0.0001043653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001069524,"about_ca_topic_score_gemma":0.0006445617,"domain_scores_codex":[0.9979855,0.00009409362,0.0001846384,0.000504321,0.0009632331,0.0002681861],"domain_scores_gemma":[0.9972975,0.0002259788,0.00004361501,0.0008922964,0.001439383,0.0001011992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005985452,0.001765782,0.1770312,0.0002099483,0.003123617,0.0008839965,0.003088125,0.001427419,0.03950305,0.1032868,0.06374302,0.6053385],"study_design_scores_gemma":[0.0003805286,0.00002413356,0.8581806,0.00001517972,0.00001462766,0.00003144864,0.00003163335,0.1141426,0.0001400213,0.005920814,0.02096408,0.000154409],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.156014,0.0006086284,0.723151,0.08266328,0.001263316,0.0005196366,0.000186079,0.0002627915,0.0353313],"genre_scores_gemma":[0.9933191,0.00003697243,0.005383733,0.0003950036,0.0002650387,0.000006004153,0.0001912466,0.000003730283,0.0003992008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8373051,"threshold_uncertainty_score":0.5229086,"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."}}