{"id":"W2579587788","doi":"10.1109/tmm.2017.2652061","title":"CrowdTranscoding: Online Video Transcoding With Massive Viewers","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Qatar National Research Fund","keywords":"Transcoding; Computer science; Multimedia; Schedule; Quality of experience; Workload; Crowdsourcing; Phone; Quality (philosophy); Key (lock); PlanetLab; Computer network; The Internet; Quality of service; World Wide Web; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007504177,0.0010991,0.000856797,0.0007556821,0.0007312267,0.001104495,0.001897257,0.0009188723,0.001916034],"category_scores_gemma":[0.003222227,0.0002641033,0.0005217845,0.0005525948,0.000809204,0.001403115,0.00217452,0.001230164,0.0006764454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005664844,"about_ca_system_score_gemma":0.0006622709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004304942,"about_ca_topic_score_gemma":0.003631143,"domain_scores_codex":[0.9993612,0.0001054763,0.00002603081,0.0001614861,0.0002479429,0.00009780522],"domain_scores_gemma":[0.998697,0.0004203235,0.00009923386,0.0002699299,0.0003383329,0.0001751574],"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":[0.001625489,0.0005788181,0.00459652,0.0003921331,0.0002103005,0.002349697,0.002276169,0.2204366,0.2010979,0.01528485,0.02029913,0.5308524],"study_design_scores_gemma":[0.0000801115,0.0002387331,0.0006449855,0.00002460513,0.00003934525,0.0006600689,0.0003342683,0.9498883,0.03017402,0.009522191,0.00832966,0.00006369783],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07499854,0.0009771849,0.9092454,0.0003314172,0.0003816706,0.0002995596,0.0002037946,0.007532521,0.006029981],"genre_scores_gemma":[0.7654374,0.0004768214,0.2263871,0.0003921454,0.0002119823,0.0001942039,0.000459883,0.0004636676,0.005976778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004304942,"threshold_uncertainty_score":0.008559763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487678475989811,"score_gpt":0.323983511580692,"score_spread":0.2752156639817109,"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."}}