{"id":"W3003692247","doi":"10.29007/br13","title":"Average SER Analysis for Layered Division Multiplexing System with Index Modulation","year":2019,"lang":"en","type":"paratext","venue":"EasyChair preprint","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Modulation (music); Transmission (telecommunications); Codebook; Reliability (semiconductor); Transmission system; Electronic engineering; Bit error rate; Algorithm; Decoding methods; Channel (broadcasting); Telecommunications; 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001837447,0.0004397863,0.0007091278,0.000529221,0.0001068383,0.00006634132,0.0006699071,0.000465124,0.00008279864],"category_scores_gemma":[0.0000244088,0.0004048775,0.0002374565,0.0004516046,0.00003436895,0.0001604867,0.0002812396,0.000491099,0.000663229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004151391,"about_ca_system_score_gemma":0.00002514807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003142623,"about_ca_topic_score_gemma":0.00004192183,"domain_scores_codex":[0.9983007,0.00004505312,0.0004874169,0.000582116,0.000264583,0.0003201583],"domain_scores_gemma":[0.9973464,0.0001363646,0.0002808293,0.002023194,0.000162886,0.00005034485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002692616,0.00001689902,0.00105615,0.0006235241,0.0007550094,4.33481e-7,0.0001671022,0.993157,0.0003234017,0.0002493317,0.0002050198,0.00341915],"study_design_scores_gemma":[0.0004539804,0.00002356043,0.003566488,0.0003428946,0.000004530501,9.252668e-7,0.0001671839,0.9908441,0.001200592,0.0000282205,0.002894514,0.0004730456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008027843,0.0003751162,0.9914668,0.00002158032,0.0004982869,0.001469292,0.0001432211,0.001292231,0.003930642],"genre_scores_gemma":[0.9874753,0.0001012401,0.008230523,0.000004613776,0.00004495274,0.0006083141,0.0005463793,0.0001229649,0.002865703],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9866725,"threshold_uncertainty_score":0.9998403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673086548651529,"score_gpt":0.248672171832158,"score_spread":0.2319413063456428,"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."}}