{"id":"W1975694774","doi":"10.1109/isbmsb.2010.5463166","title":"Geometric capacity studies for DTV transmitter identification using Kasami sequences","year":2010,"lang":"en","type":"article","venue":"","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Transmitter; Pseudorandom number generator; Interference (communication); Mathematics; SIGNAL (programming language); Transmission (telecommunications); Electronic engineering; Computer science; Topology (electrical circuits); Telecommunications; Algorithm; Engineering; Channel (broadcasting); Combinatorics","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":[0.001755877,0.001010112,0.0007204229,0.003045348,0.0007902007,0.001318341,0.001353708,0.0007038909,0.005541712],"category_scores_gemma":[0.0160356,0.0004322483,0.0004543187,0.002157113,0.002228855,0.002387763,0.001901596,0.00076777,0.0009117047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652068,"about_ca_system_score_gemma":0.0008028517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002296477,"about_ca_topic_score_gemma":0.0009557561,"domain_scores_codex":[0.9987916,0.0003547124,0.00003672652,0.0001026391,0.000402374,0.0003120996],"domain_scores_gemma":[0.9830715,0.01199706,0.001817854,0.0009801791,0.001714534,0.0004189396],"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":[0.0002933678,0.00006524393,0.001971547,0.00025165,0.00004817939,0.0004279626,0.0004463749,0.6676977,0.0159598,0.2911792,0.001874033,0.01978485],"study_design_scores_gemma":[0.00001339671,0.0001172582,0.001109763,0.00005590085,0.00003013687,0.0004829193,0.000212591,0.9272813,0.00812171,0.0609598,0.001532631,0.00008260523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4452056,0.003137762,0.4874613,0.001006869,0.000111294,0.0001191576,0.000496208,0.0004735155,0.06198823],"genre_scores_gemma":[0.988277,0.001083278,0.00844013,0.00008409975,0.00006763021,0.00007128984,0.0001520329,0.00004818434,0.001776319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005541712,"threshold_uncertainty_score":0.01853889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09780511101685986,"score_gpt":0.3220215479644031,"score_spread":0.2242164369475433,"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."}}