{"id":"W2972308422","doi":"10.1145/3309682","title":"Improving Adaptive Video Streaming through Session Classification","year":2019,"lang":"en","type":"article","venue":"Journal of Data and Information Quality","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Session (web analytics); Popularity; Quality of experience; Throughput; Computer network; The Internet; Multimedia; Quality of service; Real-time computing; World Wide Web; Telecommunications; Wireless","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":[0.001234139,0.0006391147,0.0009657398,0.001087363,0.0004115863,0.0005663785,0.0008915616,0.0005059289,0.0004750876],"category_scores_gemma":[0.002842107,0.0001664297,0.0005505723,0.0006952878,0.0001767337,0.001011517,0.0005457636,0.0008219543,0.0002496692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004070687,"about_ca_system_score_gemma":0.0006735952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004107688,"about_ca_topic_score_gemma":0.003787701,"domain_scores_codex":[0.9992396,0.0001794704,0.00005770933,0.000150126,0.0002424659,0.000130816],"domain_scores_gemma":[0.9981493,0.0005718762,0.0001692666,0.0001772835,0.0007795059,0.0001527227],"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":[0.0008190287,0.0009479467,0.02754083,0.0001435988,0.0001158712,0.000152104,0.0003859777,0.08292449,0.06840292,0.001370598,0.003357745,0.813839],"study_design_scores_gemma":[0.00001508287,0.0002347316,0.009119025,0.000009490395,0.00005028541,0.0001267704,0.00008806128,0.975369,0.01227887,0.001563022,0.00111713,0.00002839059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3478142,0.0005311572,0.6462323,0.0001977103,0.0001133809,0.0002285806,0.0003143715,0.003164307,0.001403936],"genre_scores_gemma":[0.8812921,0.0001759142,0.116036,0.00009509356,0.0000932454,0.00009858543,0.0007730281,0.0001106675,0.001325302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004107688,"threshold_uncertainty_score":0.008167565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09982095728446964,"score_gpt":0.3748448468625624,"score_spread":0.2750238895780927,"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."}}