{"id":"W2901322284","doi":"10.1109/iscc.2018.8538613","title":"Social Pre-caching for Location-dependent Requests in Vehicular Information-Centric Ad-hoc Networks","year":2018,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Cache; Computer network; Node (physics); Information-centric networking; Locality; Wireless ad hoc network; Content delivery; Provisioning; Vehicular ad hoc network; Wireless; 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":[0.0004648282,0.0001043141,0.0001139505,0.0001430726,0.0002296244,0.000244038,0.0004739932,0.00007916352,0.00000552516],"category_scores_gemma":[0.00005743727,0.00009902511,0.00005236385,0.0003455419,0.00002257535,0.001195188,0.0001259044,0.0001259958,0.00004143577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009948039,"about_ca_system_score_gemma":0.00007648833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009460993,"about_ca_topic_score_gemma":0.0001506117,"domain_scores_codex":[0.9989724,0.00004722723,0.0002967755,0.0001938503,0.0002127799,0.0002770322],"domain_scores_gemma":[0.9993441,0.00007162881,0.00009369313,0.0002368198,0.0002052402,0.00004857958],"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":[0.0002076937,0.0003292972,0.006624232,0.0001163569,0.0001032308,0.00001006429,0.01226653,0.0599784,0.0001310043,0.1661953,0.01934828,0.7346896],"study_design_scores_gemma":[0.0007167629,0.00008876652,0.00521382,0.00002583876,0.000005151533,0.000004548177,0.0000488784,0.9871308,0.00003268613,0.0009903187,0.005550725,0.000191657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04385171,0.0002388997,0.9532578,0.000712643,0.0004476341,0.0003134359,7.238087e-7,0.0001563204,0.001020824],"genre_scores_gemma":[0.9964709,0.00001994885,0.002062908,0.000941438,0.00021064,0.00003719985,0.00001049022,0.000005069081,0.00024143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9526192,"threshold_uncertainty_score":0.4038127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319270835564932,"score_gpt":0.2509067570640794,"score_spread":0.2377140487084301,"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."}}