{"id":"W2486103257","doi":"10.1145/2912845.2912849","title":"Characterizing Users in an Online Classified Ad Network","year":2016,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Dissemination; World Wide Web; Social network (sociolinguistics); Internet privacy; Information flow; Social media; Information retrieval; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001722963,0.00006117782,0.00006955231,0.00004966521,0.00003756912,0.00007242388,0.0003185113,0.00004385151,0.00002402686],"category_scores_gemma":[0.00001345871,0.0000405789,0.00001815528,0.0002198297,0.00001027727,0.0007708099,0.00006038189,0.00005600471,0.00002498785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003053494,"about_ca_system_score_gemma":0.00001584431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002284741,"about_ca_topic_score_gemma":0.0004387624,"domain_scores_codex":[0.9993515,0.00004324565,0.0001145491,0.0002158944,0.00008600378,0.0001888206],"domain_scores_gemma":[0.9995678,0.00004538352,0.00003229614,0.0002828476,0.00001598406,0.00005568625],"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":[0.00003381132,0.0001326286,0.03713271,0.00000448108,0.000007351191,0.00001808699,0.0006391411,0.0000395925,0.1153163,0.01164272,0.0008487925,0.8341843],"study_design_scores_gemma":[0.000847625,0.0002527662,0.9239007,0.0001020211,0.000002207538,0.000009989486,0.00002832486,0.03992788,0.004716688,0.003848088,0.0259819,0.0003817853],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8332993,0.00001161793,0.1617462,0.00321281,0.0008328644,0.00005886085,6.447233e-7,0.0002454943,0.0005921078],"genre_scores_gemma":[0.9880914,0.00001022354,0.01060725,0.0007743719,0.0001734459,0.000002786647,0.000001084525,0.000004639156,0.0003348039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.886768,"threshold_uncertainty_score":0.165476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05590447489307073,"score_gpt":0.257871463214954,"score_spread":0.2019669883218833,"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."}}