{"id":"W2136660391","doi":"","title":"In Pursuit of a Root","year":2007,"lang":"en","type":"article","venue":"","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Basis pursuit; Least-squares function approximation; Mathematical optimization; Norm (philosophy); Underdetermined system; Total least squares; Applied mathematics; Non-linear least squares; Differentiable function; Iteratively reweighted least squares; Algorithm; Mathematical analysis; Compressed sensing; Estimation theory; Statistics","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":[0.0008143442,0.0008065773,0.0007620687,0.0005408969,0.0004858854,0.001294369,0.0006739871,0.001473918,0.002980296],"category_scores_gemma":[0.003879361,0.0003808808,0.0003394593,0.0006824327,0.001418283,0.001606125,0.001897882,0.001629185,0.001372441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004083877,"about_ca_system_score_gemma":0.0006654464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006691384,"about_ca_topic_score_gemma":0.0005703277,"domain_scores_codex":[0.9994103,0.0001571519,0.00002402824,0.0001425714,0.0002222729,0.00004368319],"domain_scores_gemma":[0.9992255,0.0004113099,0.00007929665,0.0001103875,0.0001320068,0.00004149068],"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":[0.0003622852,0.00006797296,0.001078365,0.0003258484,0.00009418464,0.0002718215,0.0005048974,0.1959208,0.04895891,0.467557,0.01139631,0.2734616],"study_design_scores_gemma":[0.00004361253,0.0001167507,0.0003616625,0.00004060091,0.00001729466,0.0002769281,0.00009731638,0.8466518,0.009395308,0.1270565,0.0159115,0.00003070847],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008441068,0.0003817064,0.9837226,0.000427621,0.00009114515,0.00002160766,0.0000301564,0.0001972009,0.006686943],"genre_scores_gemma":[0.3580094,0.001439008,0.6210237,0.0006515699,0.0002988607,0.0001635288,0.0002170301,0.0002027488,0.01799417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002980296,"threshold_uncertainty_score":0.009970069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008835539302612154,"score_gpt":0.2345743571631913,"score_spread":0.2257388178605791,"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."}}