{"id":"W2120178331","doi":"10.1109/wcnc.2008.489","title":"Modeling User Churning Behavior in Wireless Networks Using Evolutionary Game Theory","year":2008,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Churning; Computer science; Wireless; Service provider; Wireless network; Evolutionary game theory; Revenue; Computer network; Game theory; Service (business); Distributed computing; Telecommunications; Mathematics; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001730149,0.0008202716,0.0007817247,0.000662335,0.000523245,0.001270954,0.001469529,0.001453636,0.0008987487],"category_scores_gemma":[0.005480239,0.0005132102,0.0006599796,0.0007365124,0.001142684,0.002112701,0.0007929732,0.0009770255,0.0001345593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001693818,"about_ca_system_score_gemma":0.000872651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090254,"about_ca_topic_score_gemma":0.006776019,"domain_scores_codex":[0.9987319,0.0007520658,0.00004309491,0.0001168328,0.0001647833,0.0001913005],"domain_scores_gemma":[0.9977173,0.001653343,0.0002682628,0.00009411037,0.000175906,0.00009123004],"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":[0.00002516225,0.00003696658,0.00120931,0.00001190479,0.00002195082,0.00008788447,0.00008075291,0.9654229,0.0005314448,0.03017089,0.0001030075,0.002297784],"study_design_scores_gemma":[0.000003223787,0.000007877168,0.0001035472,0.000001354822,0.000003608925,0.000009455567,0.00001128211,0.9959675,0.0000443137,0.003777458,0.0000675063,0.000002755977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.226516,0.0002509549,0.7670282,0.0003938311,0.00002811075,0.0001287054,0.00007114012,0.00008399832,0.005499081],"genre_scores_gemma":[0.9654719,0.0002582923,0.03176237,0.00005829359,0.00001624907,0.0001243458,0.00003681373,0.00001307561,0.002258623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01090254,"threshold_uncertainty_score":0.02167815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03998108050954009,"score_gpt":0.2707526384788831,"score_spread":0.2307715579693431,"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."}}