{"id":"W4392233769","doi":"10.1007/s10915-024-02464-x","title":"Anderson Acceleration as a Krylov Method with Application to Convergence Analysis","year":2024,"lang":"en","type":"article","venue":"Journal of Scientific Computing","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Acceleration; Convergence (economics); Applied mathematics; Classical mechanics; Physics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002956746,0.00009688401,0.0001893332,0.0007488006,0.0002556046,0.001323217,0.0006309673,0.000025923,0.00002445952],"category_scores_gemma":[0.00003688276,0.0000725563,0.0001183606,0.004074004,0.00003132933,0.0006318395,0.000109277,0.0001612258,0.0000390429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005337052,"about_ca_system_score_gemma":0.0001428038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006270653,"about_ca_topic_score_gemma":0.000003578005,"domain_scores_codex":[0.9984733,0.00009874352,0.0003632706,0.0003649007,0.0005201957,0.0001795476],"domain_scores_gemma":[0.9989034,0.000174767,0.0002030872,0.0002718934,0.000311313,0.0001355312],"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":[0.00003664642,0.0001158029,0.0007010758,0.00007682395,0.0005397912,0.000121235,0.0089356,0.1087658,0.02609444,0.06784859,0.001064481,0.7856997],"study_design_scores_gemma":[0.00008818176,0.0001082014,0.0007365058,0.00006160755,0.00009249825,0.0001145584,0.0001187576,0.9905154,0.0036074,0.002140459,0.002299345,0.0001170547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1099028,0.00008806743,0.8882821,0.0006413055,0.0007754754,0.00008409048,4.942262e-7,0.00004742932,0.0001783064],"genre_scores_gemma":[0.8007513,8.361774e-7,0.1988722,0.00005695629,0.0001263166,7.039558e-7,7.639683e-7,0.000003674003,0.0001872825],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8817496,"threshold_uncertainty_score":0.9997135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343121283905895,"score_gpt":0.3079481479337089,"score_spread":0.29451693509465,"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."}}