{"id":"W2079890173","doi":"10.1109/icc.2012.6364741","title":"Extending LTE to support machine-type communications","year":2012,"lang":"en","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Toronto Metropolitan University","funders":"","keywords":"LTE Advanced; Computer science; Key (lock); Computer network; Term (time); Metering mode; Telecommunications link; Engineering; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008316031,0.0004646781,0.0002545665,0.0002138561,0.0005518521,0.001241922,0.0006431607,0.001445629,0.002065884],"category_scores_gemma":[0.001716191,0.0001898129,0.0004731053,0.0002886796,0.0004040632,0.001915243,0.0007184425,0.0008947896,0.0009770427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000521548,"about_ca_system_score_gemma":0.0007616723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005383996,"about_ca_topic_score_gemma":0.005689758,"domain_scores_codex":[0.9994414,0.00009729357,0.000034365,0.00005406621,0.0001708023,0.0002020737],"domain_scores_gemma":[0.9990479,0.0002524521,0.00006208212,0.0002749409,0.0003056477,0.00005706709],"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":[0.0004189129,0.0002354977,0.0125456,0.0003118936,0.00009995325,0.003356972,0.001019118,0.07675103,0.162081,0.1967219,0.02890089,0.5175572],"study_design_scores_gemma":[0.00007820976,0.0008289734,0.008624627,0.0001988001,0.000148967,0.004908509,0.0003485638,0.2263831,0.06224839,0.08717855,0.6088853,0.0001680681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1178763,0.004061897,0.7490199,0.007534584,0.002509163,0.0002328645,0.0002803192,0.002066543,0.1164185],"genre_scores_gemma":[0.8279759,0.002891141,0.1466558,0.003400917,0.001578527,0.0001267299,0.0004135573,0.000106659,0.01685073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005383996,"threshold_uncertainty_score":0.01070529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04821973419074766,"score_gpt":0.3225157788643281,"score_spread":0.2742960446735804,"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."}}