{"id":"W2059616890","doi":"10.1109/icce.2010.5418754","title":"Mobile multimedia broadcasting applications: Speech enabled data services","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Multimedia; Broadcasting (networking); Profiling (computer programming); Synchronization (alternating current); Computer network; Human–computer interaction; World Wide Web","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004357358,0.0001124587,0.0001238568,0.00006717011,0.0001176625,0.0002628781,0.002789299,0.00007595519,0.000079582],"category_scores_gemma":[0.00003112749,0.00009421733,0.0000218072,0.0003407814,0.00002420733,0.0007928121,0.0008622732,0.0001531531,0.001048091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006347543,"about_ca_system_score_gemma":0.00005971919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000557609,"about_ca_topic_score_gemma":0.0004001802,"domain_scores_codex":[0.9987288,0.00002125374,0.0002213978,0.0005336545,0.0002265264,0.000268382],"domain_scores_gemma":[0.997381,0.000115106,0.00008255443,0.002197472,0.00008495363,0.0001388968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004907402,0.0002318003,0.003556447,0.0001277723,0.00002854244,0.00001934773,0.0008273814,0.00001253216,0.08266922,0.007832646,0.005542492,0.8991469],"study_design_scores_gemma":[0.0007739687,0.00005889057,0.0007637136,0.00002268695,0.000009960315,0.000124244,0.0002736209,0.4677287,0.02456919,0.002507719,0.5026312,0.0005361156],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03100025,0.0005220954,0.8599417,0.00024595,0.002761935,0.002327941,0.00005684286,0.001952134,0.1011912],"genre_scores_gemma":[0.317356,0.000009786853,0.6796629,0.0003424871,0.0008245393,0.00021158,0.0001322043,0.00001452659,0.001445999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8986108,"threshold_uncertainty_score":0.9997297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02012682901050998,"score_gpt":0.2710644486359172,"score_spread":0.2509376196254072,"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."}}