{"id":"W4387415411","doi":"10.1109/mnet.2023.3320660","title":"Networking Parallel Web3 Metaverses for Interoperability","year":2023,"lang":"en","type":"article","venue":"IEEE Network","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Science, Technology and Innovation Commission of Shenzhen Municipality; National Natural Science Foundation of China","keywords":"Interoperability; Computer science; Inference; Key (lock); Field (mathematics); Monopolistic competition; Knowledge management; Knowledge sharing; Data science; Computer security; World Wide Web; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006119666,0.0001213658,0.0001819933,0.00005326422,0.0003002665,0.00006163236,0.0008743198,0.0001209069,0.000002378242],"category_scores_gemma":[0.00001579606,0.000112416,0.0001013562,0.0009074137,0.00007619364,0.00009434845,0.0001902854,0.0001565916,0.0001074463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002330332,"about_ca_system_score_gemma":0.00002314022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007539654,"about_ca_topic_score_gemma":0.00003083962,"domain_scores_codex":[0.9987761,0.00004404118,0.0002121597,0.0004249448,0.00009606794,0.0004467077],"domain_scores_gemma":[0.9988499,0.0002379345,0.00006394845,0.0007379182,0.00005660819,0.00005366811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003626686,0.0001043812,0.0021413,0.00003603021,0.0001316985,0.000008836519,0.0005484736,0.03498011,0.00009297254,0.1775395,0.6817033,0.1026771],"study_design_scores_gemma":[0.0002816026,0.00006286529,0.001200884,0.00001786292,0.0000118783,0.000004477782,0.00001925988,0.2133954,0.000112487,0.2087203,0.5759376,0.0002353897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03521469,0.0003895612,0.9464492,0.003728916,0.009650867,0.0008320361,0.000004500577,0.002558242,0.001171961],"genre_scores_gemma":[0.965836,0.0001056903,0.02901924,0.0007143872,0.003434096,0.0005081437,0.000008319686,0.00001842407,0.000355636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9306214,"threshold_uncertainty_score":0.4584192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03216615470859672,"score_gpt":0.2709123210293328,"score_spread":0.2387461663207361,"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."}}