{"id":"W2057153424","doi":"10.1109/netcod.2013.6570822","title":"On multiplicative matrix channels over finite chain rings","year":2013,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multiplicative function; Linear network coding; Coding (social sciences); Matrix (chemical analysis); Mathematics; Transmitter; Lattice (music); Topology (electrical circuits); Finite field; Channel capacity; Discrete mathematics; Channel (broadcasting); Generator matrix; Computer science; Algorithm; Combinatorics; Telecommunications; Decoding methods; Physics; Mathematical analysis; Computer network","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001426632,0.0001144667,0.0001029575,0.00008077638,0.0001583363,0.0001918123,0.0008844095,0.00003428085,0.0005961339],"category_scores_gemma":[0.0000686852,0.00009239867,0.00004095158,0.0003229842,0.0000283022,0.0003637,0.0004479656,0.0001362247,0.001528837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003067136,"about_ca_system_score_gemma":0.00001264316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000190543,"about_ca_topic_score_gemma":0.000004945188,"domain_scores_codex":[0.9991847,0.00007647585,0.0001456316,0.0002650757,0.0001311522,0.0001969249],"domain_scores_gemma":[0.9986455,0.0003576311,0.00005316133,0.0007561322,0.0001040931,0.00008352562],"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":[0.000002649013,0.00009727578,0.0001770223,0.000003019161,0.00001549042,8.825181e-7,0.001789822,0.0007775666,0.001556185,0.9042458,0.01834827,0.072986],"study_design_scores_gemma":[0.0004081849,0.0000793474,0.004888771,0.00002912276,9.883643e-7,0.000001131159,0.00002295819,0.9693462,0.002312199,0.00637994,0.01626533,0.0002657741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03211416,0.0001700258,0.9178872,0.009113862,0.0002585015,0.0005934834,7.211165e-7,0.0004709928,0.03939108],"genre_scores_gemma":[0.977942,0.00009661631,0.01038989,0.002513168,0.0000387043,0.00009497529,0.000001368046,0.000007031652,0.008916227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9685687,"threshold_uncertainty_score":0.9992486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02741710375886143,"score_gpt":0.2853105657450337,"score_spread":0.2578934619861723,"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."}}