{"id":"W2171192517","doi":"10.1109/glocom.1990.116681","title":"Exploiting cyclostationary subscriber-loop interference by equalization","year":2002,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cyclostationary process; Interference (communication); Transceiver; Computer science; Transmitter; Symbol rate; Intersymbol interference; Electronic engineering; Equalization (audio); Telecommunications; Bit error rate; Engineering; Decoding methods; Wireless; Channel (broadcasting)","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":[0.0002590073,0.000361735,0.0003305581,0.0003322823,0.000242191,0.000603013,0.0004087265,0.0004656057,0.002618381],"category_scores_gemma":[0.0008878228,0.0001302789,0.0001795615,0.0003954138,0.0004593138,0.000794507,0.000538211,0.0003380782,0.0008158098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003511236,"about_ca_system_score_gemma":0.0003077965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006657115,"about_ca_topic_score_gemma":0.001080025,"domain_scores_codex":[0.9996955,0.00006284337,0.000009271961,0.00003494499,0.0001443735,0.00005302551],"domain_scores_gemma":[0.999736,0.0001477862,0.00002384871,0.00003823003,0.00004648742,0.000007670824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005292579,0.0001510192,0.001083968,0.0001581717,0.00008031529,0.0002615412,0.0002014005,0.2599747,0.2180018,0.1381569,0.005196694,0.3762042],"study_design_scores_gemma":[0.00004057802,0.000128965,0.0003844421,0.0000243797,0.00002672408,0.0002538367,0.0000215725,0.8711496,0.08915837,0.02449227,0.01429352,0.00002565685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02674453,0.0004180369,0.9580125,0.0001551544,0.00005161528,0.00002226629,0.00002258688,0.0008094225,0.01376402],"genre_scores_gemma":[0.7478766,0.0006614571,0.2376727,0.0001529018,0.0001425241,0.00004293612,0.0001046821,0.00008384163,0.01326224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002618381,"threshold_uncertainty_score":0.00875932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03150549627190388,"score_gpt":0.2223746172709773,"score_spread":0.1908691209990734,"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."}}