{"id":"W4392249554","doi":"10.1007/978-3-031-54776-8_4","title":"Fair Private Set Intersection Using Smart Contracts","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Intersection (aeronautics); Set (abstract data type); Programming language; Transport engineering; Engineering","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":[0.003555307,0.0006676067,0.001808424,0.001415414,0.003099439,0.005783179,0.002893898,0.001589112,0.01353871],"category_scores_gemma":[0.007617515,0.000945008,0.001649016,0.002838876,0.004081368,0.01270527,0.008704104,0.005047447,0.002520911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003113288,"about_ca_system_score_gemma":0.002915804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009143174,"about_ca_topic_score_gemma":0.000785273,"domain_scores_codex":[0.9957937,0.001066859,0.0001874428,0.0006217813,0.001692812,0.0006373969],"domain_scores_gemma":[0.9953518,0.002052577,0.0001662687,0.001813085,0.0003747926,0.0002414108],"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":[0.0001283316,0.00004967533,0.00008310314,0.00002927222,0.00001217242,0.00002244212,0.0001226832,0.007201552,0.0007521751,0.9633297,0.001651995,0.02661677],"study_design_scores_gemma":[0.00002366398,0.00002202841,0.00003405053,0.00001459305,0.00001330008,0.00003500069,0.00003428112,0.04481312,0.001658813,0.9487357,0.00460182,0.00001369984],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03429709,0.0003567739,0.9131622,0.0008656989,0.000184945,0.0001507522,0.0001949134,0.0009257197,0.04986174],"genre_scores_gemma":[0.6770975,0.0005085098,0.2748468,0.0002571336,0.0001956455,0.0003315475,0.0003907083,0.0004966432,0.04587545],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01353871,"threshold_uncertainty_score":0.04529154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02335195641362301,"score_gpt":0.2607964580088462,"score_spread":0.2374445015952232,"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."}}