{"id":"W2031920071","doi":"10.1145/2492517.2492662","title":"Detect inflated follower numbers in OSN using star sampling","year":2013,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Simple random sample; Sampling (signal processing); Estimator; Computer science; Random walk; Variance (accounting); Systematic sampling; Star (game theory); Sample (material); Simple (philosophy); Statistics; Poisson sampling; Sampling design; Importance sampling; Algorithm; Mathematics; Slice sampling; Monte Carlo method; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003685889,0.0005225963,0.0007671041,0.001633866,0.0006063071,0.0008583438,0.00102923,0.0007444024,0.0006501411],"category_scores_gemma":[0.01871796,0.0003879187,0.0004670203,0.001134922,0.0009213411,0.00155096,0.001181915,0.0006143238,0.0002589831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007029347,"about_ca_system_score_gemma":0.0004135538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003071329,"about_ca_topic_score_gemma":0.003920769,"domain_scores_codex":[0.9983293,0.0007626628,0.00008265302,0.0004239968,0.0002729086,0.0001284449],"domain_scores_gemma":[0.986108,0.009336972,0.001389563,0.001659602,0.001125115,0.0003806434],"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":[0.001122717,0.0002920228,0.2492443,0.0002655197,0.0002968849,0.0007454368,0.00102643,0.5322424,0.01414582,0.04490813,0.003842221,0.1518683],"study_design_scores_gemma":[0.00001521041,0.00004155497,0.006578205,0.000006591602,0.00001031387,0.0001053061,0.00007083417,0.981128,0.001708133,0.009884892,0.0004380439,0.00001295055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5221522,0.0002227724,0.475282,0.0001625566,0.00004683899,0.00007981422,0.0003458759,0.0004133366,0.001294602],"genre_scores_gemma":[0.9539969,0.00008092351,0.0447097,0.00004010568,0.00003039338,0.00004450057,0.0006003584,0.00002881047,0.0004682946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003685889,"threshold_uncertainty_score":0.0194931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02242390492234059,"score_gpt":0.2864961626567138,"score_spread":0.2640722577343732,"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."}}