{"id":"W4392174038","doi":"10.1109/mwc.004.2300015","title":"Enabling AI-Generated Content Services in Wireless Edge Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ministry of Education and Science; Arthritis National Research Foundation","keywords":"Computer science; Wireless; Computer network; Wireless network; Enhanced Data Rates for GSM Evolution; Telecommunications; Multimedia","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":[0.001014754,0.0006169195,0.0004951552,0.0005081519,0.0005676724,0.001067085,0.001398745,0.0007979776,0.0008615103],"category_scores_gemma":[0.004344634,0.0001964275,0.0002521509,0.000710797,0.0006501867,0.00189255,0.001391962,0.0009576483,0.0002984867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008489839,"about_ca_system_score_gemma":0.0007045309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003440943,"about_ca_topic_score_gemma":0.00254731,"domain_scores_codex":[0.9993931,0.0002024225,0.00003288901,0.00008959217,0.0001661965,0.0001158115],"domain_scores_gemma":[0.9982604,0.000837718,0.0001933848,0.0002430831,0.0003316813,0.0001336931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006724601,0.0002863827,0.003247684,0.0002587384,0.00006578665,0.0005857777,0.0004429486,0.6576408,0.02597354,0.03732812,0.008236407,0.2652613],"study_design_scores_gemma":[0.00001010245,0.0000403995,0.0002127091,0.00000675135,0.000007750322,0.00006601546,0.0000383255,0.9881201,0.002774789,0.007242762,0.001470788,0.000009524544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1031776,0.001013827,0.8880498,0.0004710269,0.000102232,0.0001337387,0.0000856386,0.001883366,0.005082741],"genre_scores_gemma":[0.9262426,0.0003487637,0.07186761,0.0001529713,0.00004319332,0.00005359208,0.00009197182,0.00006871876,0.001130505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003440943,"threshold_uncertainty_score":0.006841838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07779565819547266,"score_gpt":0.33519202907371,"score_spread":0.2573963708782374,"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."}}