{"id":"W3215946960","doi":"10.3390/computers10120164","title":"Click Fraud in Digital Advertising: A Comprehensive Survey","year":2021,"lang":"en","type":"article","venue":"Computers","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Realm; Categorization; Perspective (graphical); Online advertising; World Wide Web; Internet privacy; Data science; Computer security; Advertising; The Internet; Business; Artificial intelligence; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.000110445,0.0001156548,0.000165038,0.00009758323,0.00005985817,0.0004121985,0.0004447146,0.00005666546,0.000004223304],"category_scores_gemma":[0.00006829296,0.0001278501,0.00005789998,0.0007100363,0.00002656719,0.0005808258,0.0003225114,0.0001568608,0.00006766804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005614402,"about_ca_system_score_gemma":0.00006965553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009762244,"about_ca_topic_score_gemma":0.00007398149,"domain_scores_codex":[0.9989077,0.00008801874,0.0001918415,0.0004015433,0.0001793018,0.0002316037],"domain_scores_gemma":[0.9990433,0.0002849989,0.00004628252,0.0004218675,0.0001235388,0.00008002735],"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":[0.00006507819,0.0006460722,0.3112527,0.00008593544,0.0001263714,0.001509105,0.005448493,0.009582939,0.001872612,0.008615522,0.02990036,0.6308948],"study_design_scores_gemma":[0.00086709,0.00008972408,0.8676659,0.0000886216,0.000002089987,0.0001181542,0.000032175,0.1116492,0.00111083,0.002314326,0.01564943,0.0004124538],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4809397,0.0002257881,0.5157682,0.0003307544,0.001834635,0.00006615973,0.000003546255,0.0001649147,0.0006663309],"genre_scores_gemma":[0.9931269,0.000008948527,0.006017983,0.000686573,0.00006462701,0.000001934726,0.00001588264,0.000007782385,0.00006932273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6304824,"threshold_uncertainty_score":0.5213575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02702086727640573,"score_gpt":0.2475269959347288,"score_spread":0.2205061286583231,"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."}}