{"id":"W2144575370","doi":"10.1109/glocom.2005.1577837","title":"Cooperative diversity using message passing in wireless sensor networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Decoding methods; Decodes; Relay; Computer science; Fading; Cooperative diversity; Relay channel; Channel (broadcasting); Computer network; Parity bit; Wireless; Node (physics); Algorithm; 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":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001875668,0.0006080284,0.0007294912,0.0007379449,0.0004632882,0.0008890379,0.0007919638,0.0009994345,0.0003587624],"category_scores_gemma":[0.003496489,0.0003192133,0.00034084,0.001163415,0.001325536,0.001386128,0.001098176,0.0007676464,0.0001474842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005103586,"about_ca_system_score_gemma":0.0004470967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007431159,"about_ca_topic_score_gemma":0.0005696874,"domain_scores_codex":[0.9989072,0.0005339534,0.00005311959,0.000112751,0.0003297892,0.00006319735],"domain_scores_gemma":[0.9980831,0.001181163,0.0002587665,0.000227949,0.0002068027,0.00004221959],"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":[0.0001916651,0.00008347214,0.001068142,0.0003866742,0.0001342872,0.0002657188,0.000432979,0.6979809,0.01811237,0.1289746,0.001394713,0.1509745],"study_design_scores_gemma":[0.0000314392,0.0001716726,0.0001780486,0.00002546058,0.00003029669,0.00008683927,0.00002280957,0.9340659,0.00400824,0.05776253,0.003595066,0.00002167517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02825204,0.00307706,0.9657034,0.0003247734,0.0001198699,0.00005999963,0.00002373415,0.000342895,0.00209623],"genre_scores_gemma":[0.8889451,0.003361272,0.1044645,0.000133461,0.0002783576,0.0002064645,0.00006538835,0.00002937889,0.002516019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001875668,"threshold_uncertainty_score":0.009919584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05801066960294587,"score_gpt":0.2999563723088912,"score_spread":0.2419457027059453,"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."}}