{"id":"W4323825473","doi":"10.1137/21m1459265","title":"GPMR: An Iterative Method for Unsymmetric Partitioned Linear Systems","year":2023,"lang":"en","type":"article","venue":"SIAM Journal on Matrix Analysis and Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Generalized minimal residual method; Mathematics; Linear system; Block (permutation group theory); Residual; Iterative method; Applied mathematics; Matrix (chemical analysis); Iterative and incremental development; Algorithm; Computer science; Combinatorics; Mathematical analysis","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":[0.001494608,0.000134675,0.0002966057,0.000994644,0.0006978018,0.0004854346,0.0004015682,0.00005441375,0.0000138102],"category_scores_gemma":[0.00003165966,0.0001072859,0.0002221008,0.004385368,0.00002049327,0.0003170921,0.00004453015,0.0001511664,0.00005037533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002312748,"about_ca_system_score_gemma":0.00003158789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004933996,"about_ca_topic_score_gemma":0.000001463148,"domain_scores_codex":[0.9985917,0.0002130523,0.0003886911,0.000346575,0.0002302854,0.0002297514],"domain_scores_gemma":[0.998529,0.0004277419,0.0002401889,0.0003807899,0.0002100523,0.0002122055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001446014,0.0001626391,0.0001313776,0.00003156904,0.0006263854,0.000005995551,0.0002504359,0.04961716,0.0003233202,0.9126782,0.0007910823,0.03536734],"study_design_scores_gemma":[0.0003024073,0.0001487237,0.0003564448,0.000008381664,0.0003056709,0.00002467715,0.000161026,0.9355074,0.0002072568,0.02844293,0.03434815,0.0001869427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009263974,0.0001976463,0.9975051,0.0007068291,0.00005344208,0.0002940157,0.00004463834,0.0001058675,0.0001660862],"genre_scores_gemma":[0.563834,0.0009813933,0.4246865,0.0005115402,0.002275908,0.001135053,0.0002409213,0.00004976915,0.006284914],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8858902,"threshold_uncertainty_score":0.5366998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283501379380748,"score_gpt":0.3525266311840969,"score_spread":0.3296916173902895,"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."}}