{"id":"W2793054715","doi":"10.1109/tvt.2018.2816822","title":"Network Coding Aided Collaborative Real-Time Scalable Video Transmission in D2D Communications","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Computer science; Scalability; Linear network coding; Network packet; Scalable Video Coding; Scheduling (production processes); Coding (social sciences); Computer network; Decoding methods; Schedule; Real-time computing; Video quality; Distributed computing; Algorithm; Engineering","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":[0.0006144271,0.0005269407,0.0006006526,0.0004604826,0.0003850851,0.0005228908,0.0009215316,0.0005068356,0.0007298068],"category_scores_gemma":[0.001959204,0.0001929606,0.000286496,0.0008865974,0.0004371383,0.0009503872,0.000793602,0.0005764285,0.0001168333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008197407,"about_ca_system_score_gemma":0.00121467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005067602,"about_ca_topic_score_gemma":0.005576865,"domain_scores_codex":[0.9994316,0.0001603662,0.00002727864,0.0001041262,0.0001956,0.00008106758],"domain_scores_gemma":[0.9991878,0.0004485675,0.0001021622,0.0000905429,0.0001329036,0.00003799989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001360049,0.00005999642,0.0004639681,0.0001110494,0.00002523528,0.0001548644,0.00008989145,0.8933265,0.01266954,0.01582347,0.001465633,0.0756738],"study_design_scores_gemma":[0.000006681221,0.00002133951,0.00006647558,0.00000244279,0.000004314519,0.00002698133,0.00001135919,0.9954513,0.001917501,0.00223124,0.0002558529,0.000004522008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04205869,0.0004529147,0.9548043,0.0001515044,0.00003527224,0.00004935794,0.00004615414,0.0001784055,0.002223505],"genre_scores_gemma":[0.8979916,0.0004522864,0.09966096,0.00006250198,0.00002797387,0.00008632935,0.00009407243,0.00002152086,0.001602877],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005067602,"threshold_uncertainty_score":0.01007617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204935809473763,"score_gpt":0.2733818948993338,"score_spread":0.2528883139519575,"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."}}