{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001095155,0.0001860815,0.0002198585,0.0001033608,0.001383912,0.0001569078,0.001182649,0.00004982383,0.00005378284],"category_scores_gemma":[0.00006401818,0.0001950643,0.0001715199,0.0005110645,0.00005369708,0.0005517894,0.0001588334,0.0003656408,0.000001919774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001166208,"about_ca_system_score_gemma":0.00006847623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009832974,"about_ca_topic_score_gemma":0.00002770439,"domain_scores_codex":[0.9981344,0.0001557199,0.0002570808,0.0005708847,0.0005363849,0.0003455342],"domain_scores_gemma":[0.9983112,0.0001435711,0.00007706555,0.001239785,0.00009865157,0.0001297265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002185564,0.007141565,0.004338551,0.0009655148,0.00149614,0.00005675516,0.0245327,0.002419764,0.002343244,0.798739,0.02042037,0.1353608],"study_design_scores_gemma":[0.002572828,0.0006705782,0.003926977,0.00001974843,0.0001109399,0.00005284665,0.0003793313,0.007205881,0.004055928,0.5115235,0.4687177,0.0007637551],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06175157,0.0001962222,0.93301,0.001916919,0.0003544009,0.0005164794,0.00204505,0.0001768181,0.00003253466],"genre_scores_gemma":[0.9904816,0.00005679793,0.008718579,0.0003360235,0.00002041542,0.0002860277,0.00009092812,0.00000779026,0.000001846586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.92873,"threshold_uncertainty_score":0.9999161,"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."}}