{"id":"W3196996197","doi":"10.1109/isit45174.2021.9518096","title":"Construction of binary matrices for near-optimal compressed sensing","year":2021,"lang":"en","type":"article","venue":"","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Compressed sensing; Randomness; Binary number; Scheme (mathematics); Computer science; Algorithm; Theoretical computer science; Mathematics; Arithmetic","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":[0.000025023,0.00007163762,0.0001326777,0.00003226245,0.00003539349,0.00002337898,0.00003347909,0.00004678779,0.00002387794],"category_scores_gemma":[0.000008850867,0.00007438378,0.00005175517,0.00009798705,0.00003641878,0.00005351342,0.00001887197,0.00004233388,0.000001392896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008454956,"about_ca_system_score_gemma":0.00001363819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009462073,"about_ca_topic_score_gemma":0.000001649286,"domain_scores_codex":[0.999613,0.00000892093,0.0001340122,0.00008770779,0.00005585662,0.000100539],"domain_scores_gemma":[0.9996662,0.00005741356,0.00002312502,0.0001297077,0.0001043486,0.0000191881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002593597,0.00002238055,0.0001189494,0.000130292,0.00009880096,0.00002193808,0.0001045526,0.05603616,0.9101876,0.002305506,0.008342953,0.02260494],"study_design_scores_gemma":[0.0001260015,0.0000169601,0.00008003933,0.00004038297,0.00001596493,0.0000325191,0.00008640403,0.3422225,0.6541327,0.0003941664,0.002770728,0.00008166523],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6859702,0.0005359655,0.3090852,0.00003882096,0.0002628655,0.0001049252,0.000007231826,0.0006232178,0.00337155],"genre_scores_gemma":[0.600081,0.00003495329,0.3997946,0.00001450514,0.0000297818,8.494643e-7,0.000007056255,0.00001234996,0.00002486284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2861864,"threshold_uncertainty_score":0.3033283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142332588399493,"score_gpt":0.2313131769368125,"score_spread":0.2170799180968632,"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."}}