{"id":"W1955673521","doi":"10.1109/pacrim.1997.620336","title":"Multiuser detection for multiple-access communications using wavelet-packet transforms","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Wavelet packet decomposition; Network packet; Computer science; Detector; Bit error rate; Joint (building); Wavelet; Interference (communication); Wavelet transform; Projection (relational algebra); Computational complexity theory; Signal-to-noise ratio (imaging); Noise (video); Algorithm; Telecommunications; Computer network; Artificial intelligence; Engineering; Decoding methods; Image (mathematics)","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":[0.0003926198,0.0001483016,0.0001607747,0.0001873382,0.0006684992,0.0004180953,0.004360677,0.00009976641,0.00004740998],"category_scores_gemma":[0.00009470429,0.0001347442,0.0001072806,0.000732851,0.0001184527,0.001432091,0.0007557881,0.0002583808,0.00003394525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131499,"about_ca_system_score_gemma":0.00002331877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001562969,"about_ca_topic_score_gemma":0.0007036455,"domain_scores_codex":[0.9985238,0.0001477047,0.0003367976,0.0003120228,0.0002690376,0.0004105935],"domain_scores_gemma":[0.9961791,0.0006857294,0.00008252311,0.002652548,0.000275861,0.000124228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002531484,0.0006623119,0.0006700165,0.00007752261,0.00008248493,0.000001125573,0.001890924,0.004269265,0.01207817,0.02002759,0.001471327,0.9587439],"study_design_scores_gemma":[0.0006139728,0.00002999364,0.0003591955,0.00001283111,0.000003640064,0.000006693613,0.00002644153,0.9804666,0.006659575,0.000381614,0.0112572,0.0001822597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006985979,0.0001999887,0.9870519,0.00247183,0.0001028793,0.0007596363,0.000004586421,0.0003045498,0.002118638],"genre_scores_gemma":[0.7989659,0.0003484512,0.1999966,0.0001739021,0.00003195498,0.0001695382,0.000005771166,0.00001862646,0.0002892026],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9761973,"threshold_uncertainty_score":0.8103295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2497783326864255,"score_gpt":0.3734982602061373,"score_spread":0.1237199275197118,"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."}}