{"id":"W2167040808","doi":"10.1109/tcomm.2009.09.070595","title":"Relay ordering in a multi-hop cooperative diversity network","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Relay; Hop (telecommunications); Expression (computer science); Algorithm; Computer science; Computational complexity theory; Signal-to-noise ratio (imaging); Bit error rate; Diversity combining; Outage probability; Cooperative diversity; Probability of error; Selection (genetic algorithm); Mathematics; Mathematical optimization; Telecommunications; Decoding methods; Fading; Artificial intelligence","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.000402818,0.0001864045,0.0002073881,0.0001986654,0.001823553,0.000118689,0.002779271,0.0000828824,0.00002976878],"category_scores_gemma":[0.00001578231,0.0002027394,0.00008888786,0.001509748,0.0001000448,0.0005625175,0.00009290683,0.0007248698,0.0000577277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001636913,"about_ca_system_score_gemma":0.00007326561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003142142,"about_ca_topic_score_gemma":0.001621615,"domain_scores_codex":[0.9984084,0.0004698905,0.0003350303,0.0003146538,0.0001650709,0.0003069447],"domain_scores_gemma":[0.9966918,0.0003416814,0.00007851661,0.00261752,0.0001699302,0.0001005875],"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":[0.00005509781,0.003406366,0.0004716307,0.000006823072,0.0001098954,0.00001151033,0.01572574,0.5293608,0.001253433,0.08212437,0.001371644,0.3661027],"study_design_scores_gemma":[0.001741363,0.0002446513,0.007368941,0.0001945679,0.00002063612,0.00001311946,0.0001997958,0.9797278,0.000717051,0.0008094799,0.008287709,0.0006748526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001647726,0.000545882,0.9875054,0.006701718,0.0001788185,0.0003259251,0.00000333092,0.0002699202,0.002821271],"genre_scores_gemma":[0.9377321,0.003256136,0.05749284,0.001061726,0.00001038305,0.00004647986,0.000003264528,0.000008047878,0.0003890063],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9360844,"threshold_uncertainty_score":0.999476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0871327742830498,"score_gpt":0.3105994923613186,"score_spread":0.2234667180782688,"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."}}