{"id":"W2962904605","doi":"10.1017/fms.2016.32","title":"BREAKING THE COHERENCE BARRIER: A NEW THEORY FOR COMPRESSED SENSING","year":2017,"lang":"en","type":"article","venue":"Forum of Mathematics Sigma","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":268,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Homerton College, University of Cambridge; Engineering and Physical Sciences Research Council; University of Cambridge; National Science Foundation","keywords":"Compressed sensing; Computer science; Exploit; Key (lock); Sampling (signal processing); Coherence (philosophical gambling strategy); Sampling theory; Operator (biology); Theoretical computer science; Algorithm; Mathematics; Telecommunications; Sample size determination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002769253,0.0008588003,0.001110181,0.002026173,0.0009098107,0.002788036,0.001613961,0.002197741,0.003117982],"category_scores_gemma":[0.008536998,0.0005088375,0.0008326906,0.001771448,0.005261513,0.005061835,0.003604627,0.004557918,0.0007847553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225475,"about_ca_system_score_gemma":0.001119218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001085152,"about_ca_topic_score_gemma":0.0007233032,"domain_scores_codex":[0.997612,0.0007562081,0.0001119901,0.0002762173,0.001109571,0.0001339834],"domain_scores_gemma":[0.9955353,0.003182169,0.0003188347,0.0005074247,0.0003343115,0.0001219291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000243723,0.00001062067,0.00009153258,0.0001231918,0.00001689505,0.00006283987,0.000112773,0.01269353,0.002212357,0.9603454,0.001934762,0.0223716],"study_design_scores_gemma":[0.00002748476,0.00009370595,0.0001519758,0.0001106304,0.00001799779,0.0002194619,0.0000657627,0.1456655,0.001392853,0.8301826,0.02202882,0.00004320192],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001891868,0.00256945,0.9866479,0.001683625,0.0002047455,0.00002857126,0.00007180267,0.00006994158,0.006832035],"genre_scores_gemma":[0.3174731,0.01648054,0.6437445,0.004541475,0.004498533,0.0005593529,0.0003629789,0.0003465654,0.01199299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003117982,"threshold_uncertainty_score":0.01464534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02681853792031044,"score_gpt":0.2612994784288483,"score_spread":0.2344809405085379,"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."}}