{"id":"W2087286870","doi":"10.1142/s0219691313600047","title":"PHASE TRANSITIONS IN ERROR CORRECTING AND COMPRESSED SENSING BY ℓ<sub>1</sub> LINEAR PROGRAMMING","year":2013,"lang":"en","type":"article","venue":"International Journal of Wavelets Multiresolution and Information Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compressed sensing; Underdetermined system; Matrix (chemical analysis); Mathematics; Linear programming; Combinatorics; Rank (graph theory); Orthonormal basis; Code (set theory); Algorithm; Discrete mathematics; Computer science; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001581423,0.0001236645,0.0001518715,0.0003373402,0.00008487468,0.0002251249,0.00007225364,0.00006849981,0.000002371059],"category_scores_gemma":[0.00005810264,0.0001223604,0.00003025539,0.0001088957,0.00005007361,0.002772594,0.00001898779,0.0002362505,0.000001597707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000666841,"about_ca_system_score_gemma":0.00002170217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001598327,"about_ca_topic_score_gemma":0.000002926605,"domain_scores_codex":[0.9989763,0.00002120706,0.0005666174,0.00006355699,0.0002265763,0.0001457346],"domain_scores_gemma":[0.999203,0.0000287131,0.0002273621,0.00003629721,0.0004349287,0.00006972382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002722427,0.00004511924,0.00004849572,0.00003253681,0.0000228453,0.000004557568,0.0018905,0.002067022,0.08612763,0.00001042061,0.0002996359,0.909424],"study_design_scores_gemma":[0.001602991,0.00005278542,0.0003873107,0.000497291,0.000009750241,0.00030885,0.0007915391,0.9413182,0.05353933,0.00004334883,0.001294728,0.0001539333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8340068,0.0002799787,0.164903,0.0002946981,0.0001929732,0.0001346487,0.000004969682,0.00008686848,0.00009610723],"genre_scores_gemma":[0.9898241,0.0001055824,0.009832047,0.0001459593,0.00006001049,0.000002594982,0.00001856619,0.0000102587,8.660684e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9392511,"threshold_uncertainty_score":0.4989711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043818860291547,"score_gpt":0.2530346977470282,"score_spread":0.2425965091441128,"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."}}