{"id":"W2294088060","doi":"10.1109/tbc.2015.2505411","title":"LDM Core Services Performance in ATSC 3.0","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Broadcasting","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"European Regional Development Fund; Euskal Herriko Unibertsitatea; Eusko Jaurlaritza","keywords":"Digital television; Computer science; Broadcasting (networking); Digital Video Broadcasting; Digital broadcasting; Multiplexing; Digital audio broadcasting; Channel (broadcasting); Enhanced Data Rates for GSM Evolution; Electronic engineering; Telecommunications; Computer network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001100431,0.0001755202,0.0001526619,0.0002684774,0.0001432715,0.00002369758,0.0003359577,0.000112358,0.00005812181],"category_scores_gemma":[0.000005382865,0.0001404237,0.00004668052,0.0004129987,0.00005360581,0.0002443054,0.000003146922,0.0002751389,0.00011258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082794,"about_ca_system_score_gemma":0.000009656194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002105899,"about_ca_topic_score_gemma":0.0001094458,"domain_scores_codex":[0.999099,0.00001194304,0.0002751191,0.0001825687,0.000109082,0.0003222431],"domain_scores_gemma":[0.9993058,0.0001596548,0.00003402805,0.0004354856,0.00002776743,0.00003728149],"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":[0.00001356417,0.00006302784,0.002266461,0.0001086294,0.00002138794,0.00000426624,0.0002347507,0.06149485,0.02218769,0.00002766211,0.00002528208,0.9135524],"study_design_scores_gemma":[0.003866228,0.0005276887,0.03748931,0.005098883,0.00007273941,0.0002090051,0.001311878,0.5799482,0.3551633,0.0004954899,0.01340166,0.002415551],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9291041,0.0001103973,0.06722306,0.0001070831,0.000275464,0.0001172271,0.00001372696,0.00133936,0.001709604],"genre_scores_gemma":[0.995231,0.0003738939,0.004137886,0.00001676995,0.0000201619,0.00005204631,7.227815e-7,0.00003569718,0.000131847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9111369,"threshold_uncertainty_score":0.5726314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02325962740394934,"score_gpt":0.2220131720675952,"score_spread":0.1987535446636459,"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."}}