{"id":"W1940211195","doi":"10.1109/ficloud.2015.51","title":"Secure Multipath Routing Algorithm for Device-to-Device Communications for Public Safety over LTE Heterogeneous Networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer network; Computer science; Multipath propagation; Quality of service; Multipath routing; Distance-vector routing protocol; Wireless; Routing protocol; Routing (electronic design automation); Optimized Link State Routing Protocol; Wireless Routing Protocol; Telecommunications; Channel (broadcasting)","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":[0.001274145,0.0002399516,0.0002814993,0.0001105781,0.0008624041,0.0004626499,0.003059596,0.0001064521,0.000009533338],"category_scores_gemma":[0.0002531511,0.0002280151,0.0001431553,0.0006873317,0.00004609586,0.0005359557,0.001742944,0.0002061103,0.00001699617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175852,"about_ca_system_score_gemma":0.0001646502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001856011,"about_ca_topic_score_gemma":0.0006995336,"domain_scores_codex":[0.9980623,0.0002323205,0.0004939744,0.000468073,0.0001973688,0.000546025],"domain_scores_gemma":[0.9954101,0.0008460521,0.0001631182,0.002238146,0.0009576681,0.0003849179],"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":[0.00001853596,0.0001918498,0.0002841111,0.000009362456,0.00008864732,6.159203e-7,0.002026462,0.004964458,0.00003227441,0.1156855,0.008059243,0.868639],"study_design_scores_gemma":[0.0007692799,0.00007981956,0.00006017977,0.00002249027,0.000008146601,0.000004901492,0.00006121495,0.7833156,0.00003049607,0.0001749544,0.2152267,0.000246267],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001789481,0.0008591487,0.9901478,0.005670913,0.0003030293,0.0012991,0.00001795443,0.0003189701,0.001204164],"genre_scores_gemma":[0.3422323,0.0002586503,0.6518246,0.004495824,0.0001841723,0.0004403923,0.0000904443,0.00003247597,0.0004411538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8683927,"threshold_uncertainty_score":0.9298187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1289737324182765,"score_gpt":0.3425592860423984,"score_spread":0.2135855536241218,"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."}}