{"id":"W2973878198","doi":"10.3906/elk-1811-173","title":"A no-reference framework for evaluating video quality streamed through wireless network","year":2019,"lang":"en","type":"article","venue":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Codec; Video quality; Wireless network; Rate–distortion optimization; Distortion (music); Wireless; Algorithm; Pixel; JPEG; Data compression; Real-time computing; Computer vision; Block-matching algorithm; Video processing; Video tracking; Computer network; Bandwidth (computing); Telecommunications","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":[0.002573541,0.001826199,0.001256337,0.002711332,0.0005503002,0.00208991,0.002510408,0.001188011,0.001722391],"category_scores_gemma":[0.004678273,0.000368515,0.0009231946,0.001250832,0.0009273519,0.002898939,0.00159461,0.001104598,0.0007695181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001056766,"about_ca_system_score_gemma":0.001059206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004608504,"about_ca_topic_score_gemma":0.003940776,"domain_scores_codex":[0.9973841,0.0005872476,0.0002005016,0.0004295862,0.001263919,0.0001347305],"domain_scores_gemma":[0.9985074,0.0002735434,0.0002035692,0.0002006503,0.0007520919,0.00006280689],"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":[0.0004292263,0.0002920166,0.005040569,0.0008296107,0.0002378848,0.000488207,0.000281526,0.2645656,0.04389045,0.07743366,0.006081657,0.6004297],"study_design_scores_gemma":[0.00001940399,0.0004346217,0.002065613,0.00008510563,0.00009647135,0.0003588922,0.00008407595,0.962532,0.01712325,0.008395464,0.008712764,0.00009239574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003112824,0.0006787397,0.9939653,0.00005032613,0.00005209492,0.0000991949,0.0000592234,0.0003953586,0.001586919],"genre_scores_gemma":[0.2595235,0.002689203,0.7306443,0.0001945866,0.0002512894,0.0005289651,0.0006355377,0.00022134,0.005311271],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004608504,"threshold_uncertainty_score":0.0136103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06209705879069739,"score_gpt":0.3688090051219259,"score_spread":0.3067119463312286,"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."}}