{"id":"W2108526696","doi":"10.1109/lcn.2006.322070","title":"Buffer Management for 3D Image-based Rendering over Wireless Network with QoS Adaptation","year":2006,"lang":"en","type":"article","venue":"Conference on Local Computer Networks","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Rendering (computer graphics); Computer science; Tiled rendering; Image-based modeling and rendering; Mobile device; 3D rendering; Parallel rendering; Real-time rendering; Quality of service; Image quality; Software rendering; Alternate frame rendering; Artificial intelligence; Computer vision; Computer network; Image (mathematics); Computer graphics; 3D computer graphics; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003549763,0.0003682577,0.0003403813,0.00009054915,0.0002690011,0.0006091185,0.0007378321,0.0001131701,0.00001412131],"category_scores_gemma":[8.31153e-7,0.0003244548,0.0001031465,0.0003584116,0.0001069457,0.0004329453,0.000200446,0.0002530047,0.00001165105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001301918,"about_ca_system_score_gemma":0.00008712087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005951575,"about_ca_topic_score_gemma":0.00006837182,"domain_scores_codex":[0.9974945,0.000134617,0.0004148522,0.0007960353,0.0004435886,0.0007163651],"domain_scores_gemma":[0.9985991,0.0001902567,0.0001856778,0.0007059139,0.0002067991,0.0001123175],"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":[0.00009413733,0.0001286743,0.00004567643,0.0000596456,0.00003841887,0.00004072001,0.00004583238,0.6249814,0.000002354998,0.1394275,0.006820368,0.2283152],"study_design_scores_gemma":[0.001374832,0.0004438563,0.001452045,0.0002766893,0.00002022224,0.000003059416,0.00001757021,0.9911451,0.00004017911,0.002115882,0.002656419,0.0004541597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003605166,0.00003815716,0.9957507,0.000502735,0.0007046092,0.0006726313,0.000001953184,0.000275635,0.001693008],"genre_scores_gemma":[0.6116527,0.000005223478,0.3857494,0.00147469,0.0008136135,0.0001278416,0.00004367421,0.00002521748,0.0001076187],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6112922,"threshold_uncertainty_score":0.9999207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02463480792652827,"score_gpt":0.2561276927124486,"score_spread":0.2314928847859203,"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."}}