{"id":"W2388383141","doi":"","title":"An End to End Quality Optimized Error Control for Wireless Video Transmission","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Video quality; Real-time computing; Channel (broadcasting); End-to-end principle; Transmission (telecommunications); Coding (social sciences); Encoding (memory); Resilience (materials science); Error detection and correction; Scalable Video Coding; Distortion (music); Wireless; Computer network; Algorithm; Motion compensation; Artificial intelligence; Telecommunications; Bandwidth (computing); Metric (unit)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003597348,0.0002301221,0.0003143761,0.0001766699,0.0003577523,0.0001477584,0.002188916,0.0001330516,0.00002133195],"category_scores_gemma":[0.000001660737,0.0002079675,0.000137879,0.0003451886,0.00006118034,0.000293223,0.0001756084,0.0001381328,0.00004269709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003469369,"about_ca_system_score_gemma":0.00005518065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004578234,"about_ca_topic_score_gemma":0.000003459623,"domain_scores_codex":[0.9981402,0.00008168114,0.0004400658,0.0007894153,0.0001676564,0.0003809429],"domain_scores_gemma":[0.998238,0.0001542394,0.0001304216,0.001098686,0.0001633068,0.0002152986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004342396,0.0003149609,0.00002827048,0.00002211019,0.0000217329,6.02092e-7,0.0009891674,0.0001455746,0.07551077,0.03533886,0.001111383,0.8864731],"study_design_scores_gemma":[0.004710131,0.0006241617,0.002882978,0.00009409615,0.000055023,0.0000267601,0.0001586981,0.1324862,0.4147166,0.04013528,0.4026231,0.001486961],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003876276,0.00006142286,0.9917563,0.001444737,0.00003667221,0.001490195,0.00003083996,0.001096903,0.0002066695],"genre_scores_gemma":[0.3576161,0.000003943299,0.6400804,0.0006561982,0.00004276936,0.00151722,0.000007596981,0.00001349028,0.00006228854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8849862,"threshold_uncertainty_score":0.8480668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04397811528196148,"score_gpt":0.3080058653917711,"score_spread":0.2640277501098096,"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."}}