{"id":"W2122266675","doi":"10.1002/nla.547","title":"An efficient linear programming solver for optimal filter synthesis","year":2007,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sun Microsystems; Intel Corporation","keywords":"Solver; Linear programming; Deconvolution; Mathematics; Linear system; Mathematical optimization; Filter (signal processing); Algorithm; Point (geometry); Block (permutation group theory); System of linear equations; Applied mathematics; Computer science","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":[0.0005700638,0.0002054543,0.0002110936,0.0000932308,0.0003523958,0.00009979151,0.0008225828,0.00008607488,0.00003196472],"category_scores_gemma":[0.00003846343,0.0001628202,0.00009824732,0.0006672388,0.0001001927,0.0001787265,0.00008075069,0.0001635245,0.00009898704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003089596,"about_ca_system_score_gemma":0.00005897979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000499484,"about_ca_topic_score_gemma":7.816957e-7,"domain_scores_codex":[0.9982584,0.00003313034,0.0003115609,0.0006012416,0.0002767676,0.0005189741],"domain_scores_gemma":[0.9982077,0.0004225982,0.0001150036,0.0007857848,0.0001645189,0.0003044023],"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":[0.0001928168,0.001935772,0.0001562856,0.0000712863,0.00009077487,0.00001127234,0.0005614375,0.01966032,0.0006662831,0.3749789,0.0001515927,0.6015233],"study_design_scores_gemma":[0.0004335584,0.000385023,0.0001893277,0.00001639076,0.00004542754,0.00002958193,0.00007400451,0.8802984,0.01048203,0.0007964363,0.106742,0.0005077751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002773813,0.00002415555,0.9951846,0.000369033,0.00004321654,0.0009750557,0.00001593779,0.0003753484,0.0002388373],"genre_scores_gemma":[0.2162343,7.237355e-7,0.7823102,0.0002121441,0.0003339159,0.0007885004,0.00001801634,0.00002547906,0.00007669556],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8606381,"threshold_uncertainty_score":0.6639615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156288803997547,"score_gpt":0.2707725232927044,"score_spread":0.2592096352527289,"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."}}