{"id":"W4385899886","doi":"10.1109/iwcmc58020.2023.10182956","title":"Federated Learning Meets Blockchain to Secure the Metaverse","year":2023,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Metaverse; Transparency (behavior); Computer security; Human–computer interaction; Virtual reality","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004368596,0.000671512,0.001144031,0.0008925697,0.001416662,0.002238728,0.001709897,0.001809581,0.004260235],"category_scores_gemma":[0.01083766,0.0003501127,0.0008228857,0.001173235,0.001746489,0.005089691,0.004392812,0.002086139,0.0007091691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595181,"about_ca_system_score_gemma":0.003935325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003818709,"about_ca_topic_score_gemma":0.002885052,"domain_scores_codex":[0.9968686,0.001007288,0.000186024,0.0004896478,0.0009203585,0.0005281776],"domain_scores_gemma":[0.9935962,0.002562862,0.0005439981,0.002006714,0.0008997463,0.0003905069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003936135,0.0001239221,0.001583734,0.00009417908,0.00004494526,0.0003595142,0.0001846024,0.8125004,0.002568795,0.1284953,0.001385467,0.05226553],"study_design_scores_gemma":[0.00002664942,0.00004736292,0.00009061238,0.00001287423,0.000005769654,0.00004143824,0.00001902517,0.9320628,0.001548996,0.06492274,0.001211936,0.000009747529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06010749,0.0003235405,0.9333264,0.0007523169,0.00008798319,0.000131484,0.0001902809,0.0007989022,0.00428157],"genre_scores_gemma":[0.9440885,0.0001679667,0.05277961,0.00009722008,0.00002795461,0.0001266841,0.0001716559,0.00003746367,0.002503035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004368596,"threshold_uncertainty_score":0.02310359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03164721139301643,"score_gpt":0.2755010409158728,"score_spread":0.2438538295228564,"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."}}