{"id":"W2015289665","doi":"10.1007/s11761-008-0029-0","title":"Special issue on service intelligence and service science (SISS)","year":2008,"lang":"en","type":"article","venue":"Service Oriented Computing and Applications","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Service (business); Computer science; Business; Marketing","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"],"consensus_categories":[],"category_scores_codex":[0.0002231038,0.0001941658,0.0001551389,0.0002534222,0.001353824,0.0002142307,0.0002957706,0.00004847112,0.00005950986],"category_scores_gemma":[0.00001481436,0.000197009,0.00001747457,0.002893554,0.0001032152,0.0004935383,0.0002962196,0.0001564147,0.0004809105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003057915,"about_ca_system_score_gemma":0.00003702485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007994646,"about_ca_topic_score_gemma":0.0002715419,"domain_scores_codex":[0.998583,0.00000729458,0.0002614873,0.0005357219,0.0003109766,0.0003015005],"domain_scores_gemma":[0.9989147,0.00005295062,0.000159772,0.0002860342,0.0005366916,0.00004988069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002905013,0.001672524,0.02717769,0.002524549,0.0001255916,0.0000233868,0.01519327,0.006810505,0.007923082,0.3440413,0.01004493,0.5841726],"study_design_scores_gemma":[0.001244611,0.00004273121,0.0437527,0.0002742056,0.0001254518,0.00006837514,0.009380613,0.1629452,0.001125835,0.002608569,0.777243,0.001188685],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9346767,0.00006352331,0.005170594,0.0122834,0.0005725756,0.000883865,0.00000758568,0.0003974985,0.04594428],"genre_scores_gemma":[0.9568576,0.00004135612,0.0009497388,0.03195234,0.009925402,0.00004264322,0.00006753577,0.00003242361,0.0001309403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7671981,"threshold_uncertainty_score":0.9999463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02201349604215158,"score_gpt":0.2583681500423564,"score_spread":0.2363546540002048,"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."}}