{"id":"W2420658690","doi":"10.5539/mas.v10n6p238","title":"A Method Based on RTO and Selective Acknowledgement for Improving SCTP Protocol Performance in Mobile Ad Hoc Networks","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Stream Control Transmission Protocol; Computer network; Retransmission; Throughput; Mobile ad hoc network; Acknowledgement; Network packet; Timeout; Reliability (semiconductor); Packet loss; Wireless ad hoc network; Wireless; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005541045,0.0005315476,0.0004114963,0.001008753,0.0004500845,0.0004732614,0.0007803002,0.0002978931,0.0008970717],"category_scores_gemma":[0.001238351,0.0001947472,0.0003158983,0.0006068011,0.0002828219,0.0008407311,0.0002805729,0.0003709555,0.0002232824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003378464,"about_ca_system_score_gemma":0.0006817933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264185,"about_ca_topic_score_gemma":0.001144679,"domain_scores_codex":[0.999511,0.000106445,0.00003781181,0.00007969752,0.0002347338,0.00003030902],"domain_scores_gemma":[0.9993162,0.0001800576,0.00007295885,0.00008487072,0.0003143206,0.00003162369],"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":[0.0006291188,0.0002848835,0.002258061,0.0004058955,0.0001041695,0.0002490846,0.000257037,0.0512151,0.2295723,0.007894761,0.003615345,0.7035142],"study_design_scores_gemma":[0.0001947547,0.001066153,0.003356952,0.0000490192,0.0002023096,0.000762042,0.00009791903,0.8355563,0.1425883,0.003029336,0.01296061,0.0001363416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04537031,0.001033393,0.9482242,0.0001127396,0.0002259181,0.0002002316,0.00004711226,0.002459872,0.002326156],"genre_scores_gemma":[0.5166371,0.0009767236,0.477975,0.00007410229,0.000152545,0.0003097951,0.0001611991,0.0001841899,0.0035293],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001264185,"threshold_uncertainty_score":0.003001034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117027716416958,"score_gpt":0.2758943410528387,"score_spread":0.2641915694111429,"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."}}