{"id":"W2997975332","doi":"10.1109/lcomm.2019.2961312","title":"Code Design for Non-Coherent Index Modulation","year":2019,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Rayleigh fading; Constant-weight code; Algorithm; Additive white Gaussian noise; Computer science; Binary number; Modulation (music); Fading; Code (set theory); Mathematics; Decoding methods; Theoretical computer science; Set (abstract data type); Linear code; Block code; Telecommunications; Channel (broadcasting); Arithmetic; Physics","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":[0.0004980882,0.0003482646,0.0003199372,0.0005101752,0.0003593735,0.0007906401,0.0007825117,0.0005964161,0.001480427],"category_scores_gemma":[0.002357731,0.0001392911,0.0001576108,0.000696168,0.0006965326,0.0007924711,0.0008345474,0.0007167527,0.0005674082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005662086,"about_ca_system_score_gemma":0.0008065028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000404214,"about_ca_topic_score_gemma":0.0005108319,"domain_scores_codex":[0.9993698,0.0001615559,0.00003905906,0.00008696721,0.000271613,0.00007103413],"domain_scores_gemma":[0.9989744,0.000287505,0.0001724759,0.0001708234,0.0003434857,0.00005140592],"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":[0.0001558466,0.00004491903,0.0005741324,0.0002726685,0.00002606921,0.0001698389,0.0002477883,0.05633986,0.06109058,0.7312667,0.002042973,0.1477686],"study_design_scores_gemma":[0.00007190486,0.0003885031,0.0006456612,0.0001381777,0.00003091702,0.0009067354,0.0000800358,0.6320422,0.07421071,0.2586465,0.03276793,0.00007060642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02031859,0.000614212,0.9703628,0.0002191872,0.00009831353,0.00005105017,0.00005409211,0.0001353438,0.008146339],"genre_scores_gemma":[0.6538758,0.001249362,0.3354781,0.000486914,0.0001662735,0.0002832632,0.0002264472,0.00009748296,0.00813635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001480427,"threshold_uncertainty_score":0.00495255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03979673092530468,"score_gpt":0.2723266803798595,"score_spread":0.2325299494545548,"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."}}