{"id":"W1202875439","doi":"10.1007/s10208-015-9276-6","title":"Generalized Sampling and Infinite-Dimensional Compressed Sensing","year":2015,"lang":"en","type":"article","venue":"Foundations of Computational Mathematics","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":181,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council","keywords":"Sampling theory; Compressed sensing; Mathematics; Discretization; Sampling (signal processing); Nyquist–Shannon sampling theorem; Hilbert space; Key (lock); Restricted isometry property; Applied mathematics; Nyquist rate; Separable space; Property (philosophy); Calculus (dental); Algorithm; Mathematical optimization; Computer science; Mathematical analysis; 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":[0.001632299,0.00126642,0.001376927,0.001167669,0.000420843,0.001756889,0.001117214,0.001688516,0.002319856],"category_scores_gemma":[0.008301822,0.0004511721,0.0007076508,0.001856931,0.003601633,0.003008183,0.0017442,0.003327894,0.0003890666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008950475,"about_ca_system_score_gemma":0.0006845901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001877072,"about_ca_topic_score_gemma":0.001610945,"domain_scores_codex":[0.9987754,0.0006356392,0.00005418121,0.0001675677,0.0003022864,0.00006491696],"domain_scores_gemma":[0.9960646,0.002905161,0.0002510576,0.0003782317,0.0003083859,0.00009256801],"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":[0.00003528003,0.00001493691,0.0001167827,0.0001062837,0.00001879932,0.00006772652,0.000076497,0.03745153,0.0009726819,0.9445823,0.001539144,0.01501803],"study_design_scores_gemma":[0.000009102768,0.00001482922,0.00009519103,0.00002042529,0.000006136094,0.00004998374,0.00001826972,0.1374288,0.0001961135,0.860032,0.002115048,0.00001411429],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01211994,0.006346825,0.9672752,0.002014619,0.0004355117,0.00001567558,0.0001850802,0.0001208784,0.01148631],"genre_scores_gemma":[0.6866731,0.0158166,0.2767959,0.001475321,0.002890313,0.0002008655,0.0006312131,0.000129496,0.01538726],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002319856,"threshold_uncertainty_score":0.008632541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07041629827848618,"score_gpt":0.2977721634683665,"score_spread":0.2273558651898804,"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."}}