{"id":"W2102783949","doi":"10.1109/icc.2007.438","title":"Sending Correlated Gaussian Sources over a Gaussian MAC: To Code, or not to Code","year":2007,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Algorithm; Fusion center; Transmission (telecommunications); Additive white Gaussian noise; Gaussian; Coding (social sciences); Source code; Decoding methods; Code (set theory); Channel (broadcasting); Topology (electrical circuits); Telecommunications; Mathematics; Wireless; Statistics; Cognitive radio; Physics; Combinatorics","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":[0.002278232,0.001085097,0.001107049,0.0005420772,0.0005106223,0.0009522435,0.0009546112,0.001013089,0.001402994],"category_scores_gemma":[0.005629126,0.000342892,0.0004703799,0.001008751,0.001678953,0.001342268,0.001104513,0.0006376332,0.0002253181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001116631,"about_ca_system_score_gemma":0.001269061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002557835,"about_ca_topic_score_gemma":0.002750766,"domain_scores_codex":[0.9989109,0.0004473342,0.00003246609,0.0001537639,0.0002200031,0.0002354118],"domain_scores_gemma":[0.995542,0.003127078,0.0005179117,0.0002651094,0.000430851,0.0001171197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006385377,0.000121135,0.001731837,0.0002521649,0.0001149823,0.0006225536,0.0002983084,0.8387436,0.007372268,0.1107416,0.001804613,0.03755848],"study_design_scores_gemma":[0.00002800594,0.00007248623,0.000167121,0.00001019272,0.00003574373,0.00008087904,0.00005158837,0.9791557,0.001775095,0.01825687,0.0003510293,0.00001519694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.142693,0.0004666685,0.8507121,0.0006801743,0.00007794802,0.00007523761,0.0001109736,0.0001850588,0.004998972],"genre_scores_gemma":[0.9520777,0.0003882163,0.04463815,0.0001239597,0.00007122228,0.00005307839,0.00004945285,0.00002142345,0.00257686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002557835,"threshold_uncertainty_score":0.0120486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391980024361838,"score_gpt":0.3038646012847334,"score_spread":0.279944801041115,"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."}}