{"id":"W2547900636","doi":"10.1145/2988287.2989159","title":"Examining Relationships Between 802.11n Physical Layer Transmission Feature Combinations","year":2016,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Physical layer; Computer science; Throughput; MIMO; Guard interval; Channel (broadcasting); Guard (computer science); Transmission (telecommunications); Algorithm; Feature (linguistics); Layer (electronics); Computer network; Electronic engineering; Wireless; Orthogonal frequency-division multiplexing; Engineering; Telecommunications; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003388738,0.0009058418,0.0004562922,0.002764917,0.0005696947,0.001698807,0.0005484531,0.0005739111,0.002474823],"category_scores_gemma":[0.04912622,0.0004731617,0.0003577017,0.001820771,0.0005033924,0.002930844,0.0006618103,0.001354703,0.0004005384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005645335,"about_ca_system_score_gemma":0.0004713646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002219987,"about_ca_topic_score_gemma":0.002929252,"domain_scores_codex":[0.9976312,0.0008618134,0.0001469455,0.0004935948,0.0005353786,0.0003309261],"domain_scores_gemma":[0.9031342,0.08445294,0.004385146,0.001936688,0.005270065,0.0008209773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00229917,0.0009965033,0.7390953,0.0002475995,0.0005518515,0.000917747,0.0003873901,0.103919,0.01711428,0.002459164,0.002946079,0.1290658],"study_design_scores_gemma":[0.00008764842,0.001740586,0.5402619,0.00007969398,0.0007498818,0.001502315,0.001586237,0.4286645,0.01381354,0.009175736,0.002168799,0.0001691717],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812444,0.0007839139,0.01191599,0.0003777692,0.000035548,0.00006153507,0.0008235602,0.0001720492,0.004585254],"genre_scores_gemma":[0.9951345,0.0001623999,0.003737305,0.00003120382,0.00001581064,0.00002087937,0.0005215675,0.0000348547,0.0003413602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003388738,"threshold_uncertainty_score":0.01792157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0857394829124281,"score_gpt":0.2922340243682179,"score_spread":0.2064945414557898,"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."}}