{"id":"W2108635022","doi":"10.1002/wcm.1180","title":"Weighted partial network coding and its applications in wireless mesh networks","year":2011,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Linear network coding; Computer network; Network packet; Decoding methods; Quality of service; Wireless mesh network; Multiple description coding; Coding (social sciences); Multipath propagation; Jitter; Wireless; Wireless network; Algorithm; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007343983,0.0002467195,0.0003402955,0.0001350349,0.001139038,0.0001837887,0.001746028,0.0001124272,0.000006893062],"category_scores_gemma":[0.00001031174,0.0002566823,0.00004580296,0.0009310939,0.0001813495,0.0003617365,0.002770522,0.0004892414,0.000003253663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004230982,"about_ca_system_score_gemma":0.00004451927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002563596,"about_ca_topic_score_gemma":0.00009817351,"domain_scores_codex":[0.9979808,0.0004163837,0.0005643978,0.0004746901,0.0001174032,0.0004463144],"domain_scores_gemma":[0.997231,0.000608149,0.0002206985,0.001624454,0.000154126,0.0001615685],"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":[0.000004442988,0.0001588971,0.006539767,0.00001707517,0.00002520563,0.000001379901,0.003353644,0.0001504965,0.0001425314,0.7008132,0.0000342088,0.2887591],"study_design_scores_gemma":[0.0003526827,0.00004026166,0.003924851,0.000150016,0.00001000517,0.00001138804,0.0001817133,0.9917215,0.0000822956,0.0004290652,0.002784438,0.0003118392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2098998,0.01086181,0.7746459,0.0003349347,0.0001495652,0.001228562,0.000002324743,0.0003853441,0.002491761],"genre_scores_gemma":[0.9694028,0.01690172,0.01318507,0.000141194,0.00006248616,0.0002457776,0.00001827057,0.00002005696,0.00002259778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915709,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04249036169607289,"score_gpt":0.2780612519177728,"score_spread":0.2355708902216999,"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."}}