{"id":"W2121578930","doi":"10.1109/tvt.2008.927033","title":"A Convolutional-Based Distributed Coded Cooperation Scheme for Relay Channels","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Relay; Code word; Computer science; Algorithm; Convolutional code; Decoding methods; Node (physics); Redundancy (engineering); Theoretical computer science; Topology (electrical circuits); Mathematics; 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":[0.000204969,0.0001780729,0.0002002495,0.0003392124,0.0005491652,0.000070892,0.0006808212,0.0002332231,0.00001631985],"category_scores_gemma":[0.0000275221,0.000182472,0.000108099,0.001077035,0.00009023797,0.0001848659,0.000003458739,0.0003237504,0.00002930074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001274267,"about_ca_system_score_gemma":0.0001131106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.048798e-7,"about_ca_topic_score_gemma":0.000009713744,"domain_scores_codex":[0.9988301,0.00006978706,0.000272242,0.0003942571,0.0001420667,0.0002915808],"domain_scores_gemma":[0.9986454,0.00009464917,0.00007544889,0.0007602914,0.0003609545,0.00006321071],"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":[0.0001353083,0.001392247,0.00001037976,0.00001876802,0.0001343241,0.00001381535,0.0001427454,0.3506545,0.1283606,0.3767759,0.002307084,0.1400543],"study_design_scores_gemma":[0.001163925,0.0004098366,0.00001875225,0.00003701892,0.00001208926,0.00001243494,0.00000661807,0.8730234,0.1128373,0.001099875,0.01114002,0.0002387899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005381445,0.0001690109,0.9727793,0.02013573,0.0002581791,0.0005140495,0.00002230784,0.0007147506,0.00002522134],"genre_scores_gemma":[0.9563634,0.00006219064,0.04215651,0.001038465,0.00001811404,0.0002241965,0.00003229933,0.000009263461,0.00009553693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.950982,"threshold_uncertainty_score":0.7440992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440895322594596,"score_gpt":0.2698424987178483,"score_spread":0.2454335454919023,"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."}}