{"id":"W2129884074","doi":"10.1109/tmm.2013.2240670","title":"CloudMoV: Cloud-Based Mobile Social TV","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cloud computing; Mobile device; Mobile computing; Computer network; Mobile cloud computing; Exploit; Mobile Web; Quality of service; Cloudlet; Bottleneck; Mobile technology; Multimedia; Computer security; World Wide Web; Embedded system; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001810641,0.0002052926,0.0002017081,0.0001360068,0.0003387839,0.0001987228,0.0005925946,0.0001218736,0.0006957088],"category_scores_gemma":[0.000003596765,0.0001975178,0.0001870031,0.0003340042,0.00008543189,0.0005186665,0.000002986885,0.0003218037,0.002011596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009365592,"about_ca_system_score_gemma":0.0001240035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003065043,"about_ca_topic_score_gemma":0.00002007272,"domain_scores_codex":[0.9983504,0.0001392947,0.0002944199,0.0004088281,0.0004099665,0.0003970971],"domain_scores_gemma":[0.998946,0.000223259,0.00007260362,0.0004833855,0.0001234759,0.0001512901],"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":[0.00002822254,0.001635509,0.00001423683,0.00004757202,0.0000904667,0.00002004968,0.003935374,0.007266546,0.01319124,0.0003401727,0.01590616,0.9575245],"study_design_scores_gemma":[0.003077501,0.0005481377,0.001265588,0.00004004695,0.0000504532,0.000007586149,0.0003685494,0.7566548,0.2246831,0.0007625063,0.01152995,0.001011788],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01436186,0.00001376142,0.9812048,0.001478495,0.001644197,0.0004837974,0.00001352348,0.0003502909,0.0004492924],"genre_scores_gemma":[0.9529734,0.000004346085,0.04433398,0.001461672,0.0002035458,0.0004274522,0.000002625484,0.00001873705,0.0005741986],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9565127,"threshold_uncertainty_score":0.9987655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319342419825297,"score_gpt":0.2917527802506207,"score_spread":0.2685593560523677,"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."}}