{"id":"W2022424034","doi":"10.1109/mmsp.2006.285288","title":"Optimizing Voice-over-IP Speech Quality Using Path Diversity","year":2006,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Voice over IP; Computer science; Computer network; Network packet; Session Initiation Protocol; Scheduling (production processes); Packet loss; Quality of service; The Internet; Real-time computing; Server","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009367308,0.0001151604,0.0001536144,0.00009314673,0.0006194289,0.0002559591,0.002137927,0.0000681684,0.00005187705],"category_scores_gemma":[0.00002758595,0.0001126062,0.00007116508,0.0005948332,0.00006831542,0.0006895022,0.004514626,0.0002400073,0.00005554741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001596173,"about_ca_system_score_gemma":0.00006604174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00550231,"about_ca_topic_score_gemma":0.0002798508,"domain_scores_codex":[0.9981204,0.0003049028,0.0002475813,0.000342512,0.0006079587,0.0003766331],"domain_scores_gemma":[0.9981254,0.0002490174,0.00009475529,0.001295169,0.0001479627,0.00008764699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005124855,0.001194202,0.18094,0.0001040875,0.0001089331,0.0001315807,0.002285473,0.1149931,0.0104035,0.5411676,0.01930682,0.1293136],"study_design_scores_gemma":[0.0003621367,0.00001458305,0.04611446,0.00001654727,0.000002844455,0.000006193745,0.00004052807,0.9479261,0.001164526,0.002773855,0.001303877,0.0002743173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2234774,0.0001047955,0.7613072,0.000435968,0.00009410703,0.0001213398,0.000001346329,0.0002372447,0.01422058],"genre_scores_gemma":[0.7315458,0.0000130465,0.2677606,0.000109637,0.00005811015,0.000001226779,0.000002403134,0.000005293161,0.0005038552],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8329331,"threshold_uncertainty_score":0.8317884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0825997671247013,"score_gpt":0.3363379470759907,"score_spread":0.2537381799512894,"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."}}