{"id":"W2605654550","doi":"10.1109/isplc.2017.7897107","title":"Full-duplex spectrum sensing in broadband power line communications","year":2017,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Broadband; Cognitive radio; Interference (communication); Power-line communication; Transmission (telecommunications); Duplex (building); Electronic engineering; Telecommunications; Wireless; Power (physics); Real-time computing; Engineering; Channel (broadcasting); Physics","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":[0.0003185251,0.0002480217,0.0002318942,0.0001763773,0.0002511643,0.0005479621,0.0004977486,0.0006142199,0.000852656],"category_scores_gemma":[0.0007908006,0.0001572151,0.0001221417,0.0002272017,0.0004943855,0.000840746,0.0004223381,0.0003169034,0.000212083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002188839,"about_ca_system_score_gemma":0.000212409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004636823,"about_ca_topic_score_gemma":0.0005651073,"domain_scores_codex":[0.9996814,0.0001070595,0.00001192863,0.00005925378,0.0001098864,0.0000304994],"domain_scores_gemma":[0.999595,0.0002190106,0.00005570092,0.00006023044,0.00005537887,0.00001474844],"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":[0.0005530819,0.0001929293,0.003319873,0.0004636775,0.00006048755,0.0006578463,0.0005049008,0.2794462,0.3114367,0.0499393,0.002317163,0.351108],"study_design_scores_gemma":[0.00002378319,0.0002781121,0.0007879606,0.00002324184,0.00001828926,0.0006915061,0.00007332349,0.9003116,0.08087333,0.01147962,0.005409705,0.00002950936],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08392355,0.001181487,0.9085792,0.0002215792,0.0000565109,0.00002724297,0.0000230065,0.0003240224,0.005663457],"genre_scores_gemma":[0.9123132,0.0004578244,0.0853888,0.0001452219,0.00003620285,0.00002243964,0.00001601823,0.00001265285,0.001607592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.000852656,"threshold_uncertainty_score":0.00285238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029620346695032,"score_gpt":0.2819735785921389,"score_spread":0.2516773751251886,"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."}}