{"id":"W1540825607","doi":"10.1109/icspc.2007.4728602","title":"Multimedia Content Repurposing for Heterogeneous Wireless Clients","year":2007,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Repurposing; Computer science; Computer network; Wireless; Wireless network; Multimedia; Multi-frequency network; Bandwidth (computing); World Wide Web; Wi-Fi array; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004215401,0.0001057874,0.0001254414,0.00007085944,0.0001233832,0.0001032923,0.0004288102,0.00004687522,0.000003065267],"category_scores_gemma":[0.00003120542,0.00009162447,0.0001165856,0.00008772501,0.00002037332,0.0001687401,0.0001122108,0.00006145525,0.00002268301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004339279,"about_ca_system_score_gemma":0.00001537081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008680446,"about_ca_topic_score_gemma":0.00004168195,"domain_scores_codex":[0.9988966,0.00001408138,0.0002381728,0.0003280594,0.0001831687,0.0003399365],"domain_scores_gemma":[0.999196,0.0001594064,0.00006071097,0.0003611154,0.0001063234,0.0001164368],"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":[0.00009434226,0.0002262675,0.002784434,0.00001939961,0.00006310582,0.00008674151,0.0005892102,0.00008899308,0.06335013,0.01187464,0.0009418681,0.9198809],"study_design_scores_gemma":[0.002759674,0.0004269745,0.001949717,0.00007461714,0.00002269086,0.0001619115,0.000161075,0.8566368,0.1274706,0.0005333507,0.009067707,0.0007349073],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3378841,0.00008754881,0.6603355,0.00008438084,0.0006639065,0.0001890037,0.000001139823,0.0001758919,0.0005785042],"genre_scores_gemma":[0.9764814,0.000005486143,0.02127616,0.0008584217,0.00008575076,0.00001009178,0.000002688847,0.000008400165,0.001271575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9191459,"threshold_uncertainty_score":0.3736337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04839910518842593,"score_gpt":0.2659830912758814,"score_spread":0.2175839860874554,"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."}}