{"id":"W4312881501","doi":"10.1109/tsp.2022.3215651","title":"Location Estimates From Channel State Information via Binary Programming","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Binary number; Channel state information; Multipath propagation; Channel (broadcasting); Transmitter; Binary code; Binary data; Algorithm; State (computer science); Frame (networking); Real-time computing; Covariance; Mathematical optimization; Computer engineering; Theoretical computer science; Wireless; Telecommunications; Mathematics; Statistics","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":[0.00009075085,0.0001601358,0.000120913,0.0002905782,0.0005769556,0.0001037431,0.0001438663,0.00005409676,0.0000955817],"category_scores_gemma":[0.000001811344,0.0001782165,0.00003863654,0.0006436638,0.00003655262,0.0007816962,0.000002361095,0.0003237015,0.00003050139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00016521,"about_ca_system_score_gemma":0.00003600352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003013947,"about_ca_topic_score_gemma":0.000003531358,"domain_scores_codex":[0.9990979,0.00001566803,0.0002752814,0.0001308248,0.0002583917,0.000221964],"domain_scores_gemma":[0.9996937,0.00003072449,0.00005905999,0.0001071113,0.00007371848,0.00003568413],"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":[0.0000166803,0.000025197,0.000003102138,0.0000658186,0.00001263167,0.000001263485,0.0007415929,0.6883856,0.001080038,0.000001596777,0.00001994255,0.3096465],"study_design_scores_gemma":[0.000249567,0.00008211751,0.00002177088,0.00004750398,0.00002224737,0.000006150637,0.0008692944,0.9153984,0.0820234,0.0004681559,0.0005877198,0.0002236407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01382137,0.0002103648,0.9838992,0.00004018285,0.0002457408,0.0002040454,0.00002710928,0.001471763,0.00008024489],"genre_scores_gemma":[0.9975118,0.00001053624,0.002097491,0.00006713012,0.00001525802,0.0002112986,0.00004333308,0.00002852327,0.00001461192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9836904,"threshold_uncertainty_score":0.7267457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0092684687929963,"score_gpt":0.2088184357551346,"score_spread":0.1995499669621383,"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."}}