{"id":"W4387870545","doi":"10.1109/icc45041.2023.10279094","title":"Active Sensing for Localization with Reconfigurable Intelligent Surface","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Codebook; Scalability; Frame (networking); Artificial neural network; Sequence (biology); User equipment; Real-time computing; Artificial intelligence; State (computer science); Telecommunications link; Position (finance); Base station; Algorithm; Computer network","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":[0.0000395704,0.00006731597,0.00007359934,0.00005214086,0.00005325248,0.00001186419,0.00008476399,0.00004078284,0.00001043731],"category_scores_gemma":[0.00002791687,0.00005979897,0.00001177275,0.0003244574,0.0000231262,0.00009437677,0.00001269414,0.00005626516,0.00003482279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005120114,"about_ca_system_score_gemma":0.000005025379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004507507,"about_ca_topic_score_gemma":0.00002613953,"domain_scores_codex":[0.9996654,0.000004285728,0.00008349879,0.00007905982,0.00004121796,0.0001265642],"domain_scores_gemma":[0.9995884,0.0001034848,0.00001526673,0.0002280258,0.00005184764,0.00001301322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005189314,0.000001501265,0.00001016803,0.00001732015,0.00001309165,2.315374e-7,0.00007674051,0.9283956,0.002759391,0.001235843,0.0005647654,0.06692014],"study_design_scores_gemma":[0.00006060685,0.00001290213,0.00001013298,0.00001630335,0.000001541971,7.065815e-7,0.0008794888,0.5785307,0.4099636,0.001057039,0.009389879,0.00007703227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01271206,0.00003597908,0.9798105,0.0001210328,0.00004179376,0.0002061412,0.000003188798,0.002991287,0.004078015],"genre_scores_gemma":[0.9720282,0.0003125767,0.02697544,0.0000140228,0.000004326176,0.00001141671,0.00002948904,0.00003082061,0.0005937434],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9593161,"threshold_uncertainty_score":0.2438531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02561715278305318,"score_gpt":0.2525468721531204,"score_spread":0.2269297193700672,"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."}}