{"id":"W2120116321","doi":"10.1109/ssp.2012.6319834","title":"Quantized network coding for sparse messages","year":2012,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Linear network coding; Decoding methods; Quantization (signal processing); Network packet; Data compression; Multiple description coding; Coding (social sciences); Arithmetic coding; Compressed sensing","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":[0.0007126534,0.00008388737,0.0001168269,0.00002793349,0.0002738763,0.0001025948,0.0006035572,0.00002807612,0.00006106539],"category_scores_gemma":[0.00005224811,0.00007099195,0.00005376606,0.0002478632,0.00001745278,0.0004589955,0.0002799468,0.00006204708,0.00004349304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001597045,"about_ca_system_score_gemma":0.0000151649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.366524e-7,"about_ca_topic_score_gemma":0.000006945191,"domain_scores_codex":[0.9992171,0.00007967982,0.0001530611,0.0001294528,0.00008074741,0.0003399444],"domain_scores_gemma":[0.9989989,0.0003245663,0.0000468803,0.0004751209,0.00006572321,0.0000888079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003109833,0.0000239251,0.001108996,0.00000265586,0.000009783093,7.418771e-8,0.0002396412,0.00006060006,0.0003168488,0.9435666,0.02593616,0.02873161],"study_design_scores_gemma":[0.00116123,0.00006158115,0.006202199,0.00005592572,0.00001418208,0.000008328251,0.00005985722,0.3078079,0.002937965,0.003507373,0.6776304,0.0005530634],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009271448,0.00139762,0.9817086,0.001464884,0.0004913415,0.0001888491,2.352773e-7,0.0002057479,0.01361561],"genre_scores_gemma":[0.8383131,0.0003860846,0.1587881,0.0009030892,0.0002409329,0.00003670619,0.000001988248,0.000006182617,0.001323796],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9400592,"threshold_uncertainty_score":0.2894968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09860477150820754,"score_gpt":0.3253556254492502,"score_spread":0.2267508539410426,"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."}}