{"id":"W4312825914","doi":"10.1007/978-3-031-06947-5_20","title":"Maximum Multipath Diversity in Coded Cooperative Relay Networks","year":2022,"lang":"en","type":"book-chapter","venue":"Signals and communication technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relay; Computer science; Cooperative diversity; Decoding methods; Node (physics); Algorithm; Diversity gain; Coding (social sciences); Channel (broadcasting); Relay channel; Multipath propagation; Computer network; Theoretical computer science; Fading; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000285735,0.0004835844,0.0004809283,0.0004725933,0.000230898,0.000901579,0.0007076727,0.0006386343,0.002191447],"category_scores_gemma":[0.001295224,0.0003577496,0.0001688233,0.001472086,0.0008476853,0.0009742002,0.0006660409,0.001009318,0.0006201882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006347201,"about_ca_system_score_gemma":0.0003867803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003813577,"about_ca_topic_score_gemma":0.000505766,"domain_scores_codex":[0.9997726,0.00005989177,0.000004877423,0.00002725316,0.0001144838,0.00002088914],"domain_scores_gemma":[0.9995146,0.0003674956,0.00001772107,0.00004024577,0.0000498964,0.000009981916],"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":[0.00009019749,0.00002526405,0.00008570076,0.0003749951,0.00002928507,0.0001098729,0.0001737326,0.219441,0.01161439,0.5184747,0.01205465,0.2375262],"study_design_scores_gemma":[0.00003124136,0.00009067488,0.0002914053,0.0001621758,0.00002809162,0.0003517701,0.00005750749,0.2892924,0.006657138,0.6535635,0.04943014,0.00004400095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02456116,0.0262523,0.7725201,0.0009035073,0.0005298681,0.00003433464,0.0001331123,0.0004503996,0.1746152],"genre_scores_gemma":[0.7186024,0.03153276,0.1451315,0.0004019077,0.001099066,0.0002057549,0.0002120461,0.0001845971,0.10263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002191447,"threshold_uncertainty_score":0.007331133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03848897724243196,"score_gpt":0.2546081736918402,"score_spread":0.2161191964494083,"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."}}