{"id":"W3176170052","doi":"10.1109/aiiot52608.2021.9454203","title":"Mutually Private Verifiable Machine Learning As-a-service: A Distributed Approach","year":2021,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Correctness; Machine learning; Verifiable secret sharing; Commit; Artificial intelligence; Distributed computing; Service (business); Service provider; Usability; Software engineering; Human–computer interaction; Database; Programming language; Set (abstract data type)","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":[0.0165561,0.0009900753,0.001490274,0.001769166,0.002552987,0.00759108,0.004864423,0.003052063,0.006448481],"category_scores_gemma":[0.03194179,0.001246175,0.001756397,0.001235948,0.005396855,0.01403155,0.01097708,0.00640739,0.002025559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003284111,"about_ca_system_score_gemma":0.006049563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001415749,"about_ca_topic_score_gemma":0.001340262,"domain_scores_codex":[0.9839144,0.006602964,0.000960775,0.002191473,0.005116957,0.001213508],"domain_scores_gemma":[0.9541655,0.01857914,0.002426899,0.01893311,0.004563589,0.001331786],"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":[0.0004155711,0.0001862044,0.0006905262,0.0002975711,0.0001033945,0.0005077805,0.0007221255,0.05468514,0.009163646,0.8458928,0.004809408,0.08252569],"study_design_scores_gemma":[0.0001629881,0.0001354461,0.0001077901,0.00007571919,0.00008080423,0.0003256755,0.0001415664,0.4557946,0.01215958,0.5075665,0.02338083,0.00006840757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003213252,0.0001380453,0.9926034,0.0008441312,0.00006152349,0.0001716171,0.00003918032,0.001164056,0.001764869],"genre_scores_gemma":[0.3685687,0.0006014345,0.6207979,0.0007099544,0.0003552881,0.0006955746,0.0002217796,0.0005815508,0.00746784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0165561,"threshold_uncertainty_score":0.08755809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246312768905294,"score_gpt":0.2222625512052971,"score_spread":0.2097994235162442,"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."}}