{"id":"W4315497913","doi":"10.3389/fcomp.2022.1068478","title":"Toward immersive communications in 6G","year":2023,"lang":"en","type":"article","venue":"Frontiers in Computer Science","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Carleton University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Virtual reality; Haptic technology; Multimedia; Entertainment; Human–computer interaction; Reliability (semiconductor); Telecommunications network; Immersive technology; Telecommunications; Simulation; Power (physics)","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001546678,0.0001561248,0.000228361,0.001306184,0.0002778474,0.0003067632,0.005809286,0.00005422293,3.451392e-7],"category_scores_gemma":[0.00005239441,0.0001656077,0.00005133267,0.007124222,0.0004551834,0.001069639,0.00314031,0.0003028648,0.00007819667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002379958,"about_ca_system_score_gemma":0.0002810147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005570986,"about_ca_topic_score_gemma":0.000004020534,"domain_scores_codex":[0.9976588,0.00009474224,0.0003464332,0.0006866538,0.0004440943,0.0007692836],"domain_scores_gemma":[0.9982059,0.0001227856,0.00008138769,0.001381483,0.00008545018,0.0001229839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000665571,0.0001871365,0.1119526,0.00003595083,0.00001176973,0.0002120334,0.02474966,0.006269619,0.0002970449,0.007208592,0.0764821,0.7725868],"study_design_scores_gemma":[0.0002630031,0.00002991292,0.03812061,0.00005372591,6.717792e-7,0.000008087673,0.00006392619,0.9508739,0.0001630638,0.00688451,0.0033176,0.000221007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01725641,0.0001684295,0.9598264,0.003513294,0.01808735,0.0001831436,1.83216e-7,0.0001886715,0.0007761905],"genre_scores_gemma":[0.3945607,0.00007911702,0.6043636,0.0005629074,0.0003581659,0.00001716315,0.000002565178,0.000009940904,0.0000457931],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9446043,"threshold_uncertainty_score":0.9995698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.044456224061562,"score_gpt":0.285694358639188,"score_spread":0.241238134577626,"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."}}