{"id":"W2946933108","doi":"10.1109/lcnsymposium47956.2019.9000671","title":"A Longitudinal Analysis of Online Ad-Blocking Blacklists","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blocking (statistics); Tracking (education); Computer science; Metric (unit); The Internet; Block (permutation group theory); JavaScript; Computer security; World Wide Web; Computer network; Business; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002852348,0.0001850985,0.0005028563,0.000683934,0.00003028017,0.0001430297,0.001128532,0.000197383,0.00006734558],"category_scores_gemma":[0.00003971711,0.0001695068,0.0003937173,0.0010793,0.00002308609,0.0001236078,0.001271025,0.0003532798,0.00001645171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005737658,"about_ca_system_score_gemma":0.0001096873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006659128,"about_ca_topic_score_gemma":0.0005616312,"domain_scores_codex":[0.9984255,0.00005166531,0.0003488921,0.0006298997,0.0003722675,0.0001717505],"domain_scores_gemma":[0.9981217,0.00008945852,0.0003089724,0.001250892,0.0001773921,0.00005154203],"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":[0.00007439739,0.001131064,0.2509765,0.0009635842,0.01311505,0.00005583966,0.004350894,0.6075968,0.001912845,0.01273735,0.002854644,0.1042309],"study_design_scores_gemma":[0.0001018173,0.00004176697,0.1818386,0.00006823579,0.0005477698,0.000002189993,0.00000828516,0.8152136,0.0006584119,0.0009584908,0.0003027865,0.0002581339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2771201,0.0001863635,0.7195062,0.0002947003,0.001113856,0.0001285182,0.0000200858,0.0001663837,0.001463773],"genre_scores_gemma":[0.9761247,0.00002969555,0.0230881,0.00005432967,0.00006340494,0.000003124965,0.00004349087,0.000007257555,0.0005858853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6990046,"threshold_uncertainty_score":0.6912286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03318950853451973,"score_gpt":0.2902060393501629,"score_spread":0.2570165308156431,"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."}}