{"id":"W4283775510","doi":"10.1145/3477531","title":"Accountable Private Set Cardinality for Distributed Measurement","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Privacy and Security","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Correctness; Set operations; Computer security; Bloom filter; Set (abstract data type); Anonymity; Overhead (engineering); Adversary; Cardinality (data modeling); Distributed computing; Theoretical computer science; Computer network; Algorithm; Data mining","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":[0.008150715,0.00124361,0.001309096,0.001448571,0.002445588,0.005189174,0.004401866,0.001995361,0.005361172],"category_scores_gemma":[0.02281676,0.001039374,0.001900477,0.002424337,0.005380723,0.01435521,0.01100034,0.00717803,0.001556058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003449369,"about_ca_system_score_gemma":0.003636436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110131,"about_ca_topic_score_gemma":0.0009315512,"domain_scores_codex":[0.9858806,0.004102137,0.001195437,0.002086296,0.005789645,0.00094585],"domain_scores_gemma":[0.9787901,0.006469842,0.002048809,0.01077275,0.001360588,0.0005579302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001758648,0.00008415343,0.0005393974,0.0001230836,0.00004407245,0.0001209252,0.000337306,0.03001401,0.005252307,0.9299564,0.002205737,0.03114675],"study_design_scores_gemma":[0.00007848356,0.0001292841,0.0002688804,0.00008208229,0.00005209508,0.0002578892,0.0001158191,0.2921959,0.01639843,0.6658159,0.02451052,0.00009476498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003159039,0.0001242292,0.992285,0.0003995932,0.00007326578,0.0001329191,0.00009906037,0.0008548162,0.002872107],"genre_scores_gemma":[0.3782503,0.0004136337,0.612756,0.0004934526,0.000314131,0.001277139,0.000459234,0.0003685417,0.005667511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008150715,"threshold_uncertainty_score":0.0431056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04555161940701603,"score_gpt":0.2702114391367826,"score_spread":0.2246598197297666,"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."}}