{"id":"W2951998030","doi":"10.1051/m2an/2018048/pdf","title":"Nonintrusive approximation of parametrized limits of matrix power algorithms – application to matrix inverses and log-determinants","year":2019,"lang":"en","type":"article","venue":"Springer Link (Chiba Institute of Technology)","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Mathematics; Interpolation (computer graphics); Logarithm; Inverse; Matrix (chemical analysis); Applied mathematics; Approximation error; Algorithm; Affine transformation; Mathematical analysis; Computer science; Pure mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003810888,0.0002257203,0.000576869,0.0009925447,0.00004901315,0.00001983126,0.001003097,0.0003030112,0.000007772893],"category_scores_gemma":[0.0001878035,0.0002159671,0.00009278188,0.001359842,0.0002998261,0.0004472839,0.0005338396,0.0002095795,0.00003461682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002957527,"about_ca_system_score_gemma":0.00008005118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002543637,"about_ca_topic_score_gemma":0.000002597206,"domain_scores_codex":[0.9982484,0.00002447544,0.0006659811,0.0005199806,0.0002737534,0.0002674321],"domain_scores_gemma":[0.9980499,0.00005711462,0.0006111555,0.0009768079,0.0002351145,0.00006992704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001318476,0.0003483984,0.01003028,0.0007969071,0.0001387448,0.000009027249,0.000636408,0.0007168533,0.1796296,0.5396765,0.00002428995,0.2678611],"study_design_scores_gemma":[0.002089509,0.0009374418,0.003404262,0.0004234874,0.0000602464,0.00004619848,0.0001326264,0.03576038,0.9286004,0.02258296,0.005332052,0.0006303916],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8283024,0.0001930832,0.1692818,0.0004357286,0.0004541494,0.0008769073,0.00001487476,0.0001542774,0.0002867787],"genre_scores_gemma":[0.7564433,0.00004348019,0.2433704,0.00001725405,0.00001943051,0.0000277649,0.000001910668,0.00001112043,0.00006540615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7489708,"threshold_uncertainty_score":0.8806885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009443246146090777,"score_gpt":0.2577361175949487,"score_spread":0.2482928714488579,"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."}}