{"id":"W1999997491","doi":"10.1145/1462173.1462178","title":"Algorithm 890","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Mathematical Software","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Benchmarking; MATLAB; Algorithm; License; Software; Compressed sensing; Software testing; Data mining; Computer engineering; Computational science; Programming language; Operating system","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":[0.001138623,0.001470519,0.00117446,0.001800576,0.001107734,0.002754199,0.001827371,0.001810238,0.06822247],"category_scores_gemma":[0.007167069,0.0004178299,0.001055831,0.001894784,0.0007289435,0.002024174,0.002618477,0.001631538,0.04654084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001028757,"about_ca_system_score_gemma":0.00259065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002297885,"about_ca_topic_score_gemma":0.00348526,"domain_scores_codex":[0.9983626,0.000313439,0.0001469684,0.0005209428,0.0004951204,0.0001609696],"domain_scores_gemma":[0.9984394,0.0004171556,0.0000654449,0.0004737428,0.0005340609,0.00007023798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004149213,0.0001785531,0.001153541,0.000453147,0.0001185978,0.0001259277,0.0001078096,0.06562675,0.0049364,0.08480579,0.1049622,0.7371163],"study_design_scores_gemma":[0.0002966749,0.0002753415,0.0009428411,0.0002051824,0.0000812264,0.0008781124,0.000169437,0.5771286,0.01392976,0.1842415,0.2217574,0.00009386588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005191615,0.0007148424,0.946084,0.0007027122,0.0004954842,0.0004216947,0.002557488,0.005746874,0.03808533],"genre_scores_gemma":[0.07834856,0.0009046142,0.8388426,0.000970588,0.0003019992,0.001226036,0.01533151,0.003096196,0.06097787],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06822247,"threshold_uncertainty_score":0.2282269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595090383972415,"score_gpt":0.2412137621590857,"score_spread":0.2252628583193615,"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."}}