{"id":"W2104246885","doi":"10.1109/wimob.2009.23","title":"Media Caching Support for Mobile Transit Clients","year":2009,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cache; Smart Cache; Computer network; False sharing; The Internet; Cache algorithms; Wireless; Point (geometry); CPU cache; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002104157,0.0000827662,0.0001104845,0.00005337281,0.00009305335,0.00008669557,0.0004341449,0.00003342051,0.00001740492],"category_scores_gemma":[0.00001366508,0.0000711281,0.0001013626,0.00008465206,0.000006962408,0.0002886505,0.00002108673,0.00006459674,0.00003322309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000152324,"about_ca_system_score_gemma":0.00002544768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001982591,"about_ca_topic_score_gemma":0.000009527074,"domain_scores_codex":[0.9992213,0.00001411091,0.000140669,0.0002455484,0.0001573077,0.0002210541],"domain_scores_gemma":[0.999525,0.00007120481,0.00002313144,0.0002655143,0.00003529986,0.00007986973],"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":[0.00004356952,0.0003761364,0.0004259575,0.00001502524,0.00003267235,0.00003651115,0.003375859,0.001563859,0.0146883,0.1050802,0.01471934,0.8596426],"study_design_scores_gemma":[0.007608532,0.003899173,0.0143366,0.00009743338,0.00009801042,0.000178089,0.0005785191,0.7885075,0.01718879,0.02320549,0.1418366,0.002465366],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06684831,0.00004441712,0.9229454,0.0006040304,0.0004818421,0.0002194856,0.000003891905,0.0002906763,0.008561923],"genre_scores_gemma":[0.9904253,0.000004541944,0.006329312,0.001757804,0.00006535368,0.00001255903,0.000005973527,0.000003503282,0.001395672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.923577,"threshold_uncertainty_score":0.290052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702428029755242,"score_gpt":0.2480453038135148,"score_spread":0.2310210235159623,"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."}}