{"id":"W4312465480","doi":"10.1109/pimrc54779.2022.9977859","title":"Sensing via Orthogonal Time Frequency Space Signalling and Reconfigurable Intelligent Surface","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Transmission (telecommunications); Electronic engineering; Radar; Frequency modulation; Modulation (music); Range (aeronautics); Base station; Tunable metamaterials; Orthogonal frequency-division multiplexing; Real-time computing; Acoustics; Telecommunications; Engineering; Radio frequency; Channel (broadcasting); Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005346013,0.0003444781,0.0003204559,0.0002331778,0.0008519134,0.0001382928,0.0007009655,0.00009756065,0.001081743],"category_scores_gemma":[0.00002617092,0.0004116768,0.0001258019,0.0003219096,0.0002315109,0.0003361771,0.0001771516,0.0009085801,0.00005749622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005186292,"about_ca_system_score_gemma":0.00006365775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001289017,"about_ca_topic_score_gemma":0.00001586134,"domain_scores_codex":[0.9978933,0.0002313115,0.0005107487,0.00046616,0.000535271,0.0003631807],"domain_scores_gemma":[0.9985107,0.0003932375,0.0001412835,0.0005559425,0.0001672644,0.0002316392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002735687,0.0009369099,0.001468238,0.000151738,0.001620664,0.00005900103,0.02516883,0.2781399,0.6411743,0.004032474,0.0234663,0.02350804],"study_design_scores_gemma":[0.001745612,0.0007804403,0.0003436817,0.0001989241,0.0001688203,0.001445084,0.008877333,0.5878634,0.0228002,0.000730211,0.3730727,0.001973642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519652,0.006935267,0.001551436,0.0047507,0.002702856,0.001129125,0.001505561,0.0006406078,0.02881924],"genre_scores_gemma":[0.9920571,0.003344631,0.00117845,0.0002109705,0.000191431,0.0001663215,0.0002878987,0.00008058727,0.00248254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6183741,"threshold_uncertainty_score":0.9998335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269102077563803,"score_gpt":0.2413137893290444,"score_spread":0.2286227685534064,"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."}}