{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":58,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":58,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"65d2aabcbca5","filters":{"venue":"Numerical Linear Algebra with Applications"}},"results":[{"id":"W2104744926","doi":"10.1002/nla.622","title":"Numerical solution of large‐scale Lyapunov equations, Riccati equations, and linear‐quadratic optimal control problems","year":2008,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":344,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Algebraic Riccati equation; Mathematics; Cholesky decomposition; Linear-quadratic regulator; Riccati equation; Lyapunov equation; Linear-quadratic-Gaussian control; Linear system; Applied mathematics; Lyapunov function; Optimal control; Mathematical optimization; Differential equation; Mathematical analysis; Nonlinear system","retraction":null,"screen_n_in":null,"score":{"opus":0.0146462960125644,"gpt":0.2505833551941164,"spread":0.235937059181552,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001287262,0.0002468043,0.0003791799,0.00008675022,0.0004776341,0.00001892463,0.0001651392,0.00008148538,0.0002201135],"category_scores_gemma":[0.00001631022,0.0002108702,0.0001010918,0.0006533238,0.0002069405,0.00018483,0.00003580463,0.0002999956,0.00006986359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002352302,"about_ca_system_score_gemma":0.0001222168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008205155,"about_ca_topic_score_gemma":0.000001436037,"domain_scores_codex":[0.9982565,0.00008741492,0.0005498402,0.0004498666,0.0002979879,0.0003583776],"domain_scores_gemma":[0.9986252,0.0002474151,0.0002897008,0.0003814654,0.000223184,0.0002329893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006199517,0.009695048,0.07125976,0.0002788591,0.001080051,0.000004237592,0.003812341,0.5084563,0.003976566,0.3356605,0.003612388,0.06154397],"study_design_scores_gemma":[0.001410291,0.0001871563,0.001110132,0.00002167028,0.0001059147,0.000008141072,0.0001310801,0.9899899,0.0004135699,0.0008899947,0.005387137,0.000345006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01132833,0.000178269,0.9858865,0.0009566158,0.00002904279,0.0009770945,0.00007594128,0.00008783016,0.0004803584],"genre_scores_gemma":[0.9670925,0.0000210649,0.03111456,0.0001274456,0.00033724,0.000779829,0.000249752,0.00003566723,0.0002419432],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9557642,"threshold_uncertainty_score":0.8599039,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099359799","doi":"10.1002/nla.515","title":"Preconditioners for the discretized time‐harmonic Maxwell equations in mixed form","year":2007,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":106,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Discretization; Schur complement; Eigenvalues and eigenvectors; Finite element method; Applied mathematics; Maxwell's equations; Saddle point; Saddle; Mathematical analysis; Mathematical optimization; Geometry; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.006816845117285113,"gpt":0.24769655799835,"spread":0.2408797128810649,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002022514,0.0001258376,0.0001538184,0.0000649938,0.0002290565,0.00003118965,0.0001940459,0.00002777914,0.0003180029],"category_scores_gemma":[0.000007672471,0.00008716616,0.000101076,0.0005614321,0.00006950387,0.00005000603,0.00001750439,0.0001369445,0.00008039531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002573206,"about_ca_system_score_gemma":0.00004131343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007085787,"about_ca_topic_score_gemma":0.0000173731,"domain_scores_codex":[0.9990743,0.00001429771,0.0002563388,0.0002390419,0.0001169459,0.0002990312],"domain_scores_gemma":[0.9989317,0.0005601726,0.00009268005,0.0002867673,0.00004922624,0.00007947387],"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":[0.000484107,0.002818185,0.01766743,0.0000697932,0.001461289,0.000001620557,0.001210218,0.00679722,0.01997737,0.4155933,0.006537739,0.5273817],"study_design_scores_gemma":[0.01040351,0.001258962,0.0541955,0.000109326,0.001947411,0.000009776922,0.002650129,0.532367,0.02545705,0.1298745,0.2388367,0.002890172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01026965,0.00003048354,0.9851048,0.002013191,0.00001021741,0.0007344587,0.00005239845,0.00004132807,0.001743492],"genre_scores_gemma":[0.9846844,0.000001419745,0.01201499,0.0001353944,0.0002089783,0.00133747,0.0005526612,0.00002296349,0.001041693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9744148,"threshold_uncertainty_score":0.3554533,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2945154147","doi":"10.1002/nla.559","title":"Distance‐two interpolation for parallel algebraic multigrid","year":2007,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Lawrence Livermore National Laboratory; U.S. Department of Energy","keywords":"Multigrid method; Scalability; Interpolation (computer graphics); Parallel computing; Convergence (economics); Computer science; Mathematics; Algorithm; Computational science; Partial differential equation","retraction":null,"screen_n_in":null,"score":{"opus":0.01267897775696264,"gpt":0.2831024832464812,"spread":0.2704235054895186,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002863577,0.0001595212,0.0001460855,0.0001218798,0.0002650243,0.00007593315,0.0004091002,0.00004985603,0.00001144947],"category_scores_gemma":[0.00003632034,0.0001408147,0.00007079913,0.0008615214,0.00004654997,0.0002332129,0.00005818829,0.0001111041,0.00006062531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003923979,"about_ca_system_score_gemma":0.00007194395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008648601,"about_ca_topic_score_gemma":0.00001755472,"domain_scores_codex":[0.9986317,0.00002011985,0.0003218886,0.0004724356,0.000259705,0.0002942121],"domain_scores_gemma":[0.9987648,0.0002792467,0.0001357905,0.0004143321,0.0002376588,0.0001682141],"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":[0.0001183196,0.0003076294,0.0006893945,0.00002046286,0.0000439732,0.000001273144,0.0001824801,0.01144566,0.001163038,0.853386,0.0008712664,0.1317705],"study_design_scores_gemma":[0.001469993,0.0002835989,0.00569259,0.00001341764,0.00002380699,0.00002292134,0.00002819663,0.8068739,0.001674093,0.02068299,0.1627712,0.000463342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00102146,0.00007874627,0.9964535,0.0008213416,0.0000869726,0.000890103,0.000008910748,0.0001979663,0.0004409669],"genre_scores_gemma":[0.3980796,0.000002426749,0.6004215,0.0004429102,0.0003332352,0.000392397,0.0001264595,0.00001315893,0.0001882999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8327031,"threshold_uncertainty_score":0.5742258,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1919986261","doi":"10.1002/nla.1845","title":"The power and Arnoldi methods in an algebra of circulants","year":2012,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":46,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Centre International de Recherche sur le Cancer","keywords":"Mathematics; Circulant matrix; Algebra over a field; Linear algebra; Scalar (mathematics); Dimension (graph theory); Matrix (chemical analysis); Numerical linear algebra; Pure mathematics; Discrete mathematics; Numerical analysis; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.03708464711442809,"gpt":0.3759844170192982,"spread":0.3388997699048701,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003873105,0.0001386419,0.0002199309,0.00005742861,0.0001797828,0.00002335342,0.0002181193,0.00006979756,0.00004675104],"category_scores_gemma":[0.00005222189,0.00009383253,0.00004011528,0.0004767397,0.0001757899,0.0001207461,0.00004311508,0.0001862586,0.00002327299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933338,"about_ca_system_score_gemma":0.00002295206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008217239,"about_ca_topic_score_gemma":0.000004881106,"domain_scores_codex":[0.998858,0.0001229791,0.00036401,0.0002145119,0.0001642384,0.0002762274],"domain_scores_gemma":[0.9983444,0.0006514193,0.0001573457,0.0005694801,0.00008783151,0.000189585],"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":[0.0000265218,0.0008466564,0.01172386,0.00002242376,0.00003772018,2.28108e-7,0.000569194,0.000005778496,0.003520155,0.9642148,0.0001842586,0.01884839],"study_design_scores_gemma":[0.002987082,0.0005433368,0.3380848,0.00009427642,0.0003624285,0.0002039973,0.002849324,0.007678473,0.01365124,0.4646793,0.1671615,0.001704263],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.242032,0.0004009398,0.7520065,0.001409926,0.00002797471,0.001324219,0.00003430971,0.0001577201,0.002606354],"genre_scores_gemma":[0.7490854,0.00001556734,0.2501366,0.0001200062,0.00004719261,0.0005119505,0.00001148138,0.00002534731,0.00004642586],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5070534,"threshold_uncertainty_score":0.3826379,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2165397333","doi":"10.1002/nla.2017","title":"A family of constrained pressure residual preconditioners for parallel reservoir simulations","year":2015,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; CMG Reservoir Simulation Foundation; University of Calgary","keywords":"Preconditioner; Residual; Newton's method; Scalability; Scale (ratio); Reservoir simulation; Applied mathematics; Mathematics; Residual oil; Mathematical optimization; Computer science; Algorithm; Iterative method; Nonlinear system; Petroleum engineering; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.04498031905365354,"gpt":0.3201237360138019,"spread":0.2751434169601484,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001290057,0.0001791863,0.0003015925,0.00007863233,0.00007210971,0.00001231491,0.000209799,0.00008566739,0.00001513795],"category_scores_gemma":[0.0002528907,0.0001633814,0.00005459661,0.0004884801,0.0001600972,0.0001175771,0.00002440523,0.0001511474,0.00001170088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003420378,"about_ca_system_score_gemma":0.00008643659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002044633,"about_ca_topic_score_gemma":5.967454e-7,"domain_scores_codex":[0.9988049,0.00003573769,0.0004367073,0.0002319406,0.0002729229,0.0002178167],"domain_scores_gemma":[0.998015,0.001017903,0.000119176,0.0003299937,0.0003271686,0.0001907994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004284692,0.0000879128,0.00004720181,0.0001019978,0.00009116024,1.816571e-7,0.00009370592,0.9695163,0.0002815648,0.02776967,0.0008522099,0.001115261],"study_design_scores_gemma":[0.001010538,0.0001888819,0.0001541953,0.00002664996,0.0001035753,0.00000565739,0.0001275347,0.8768577,0.0005155364,0.09605393,0.02466179,0.0002940412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002051884,0.0001299907,0.994801,0.0002173892,0.00003914014,0.001144907,0.0003934118,0.0002876653,0.0009346046],"genre_scores_gemma":[0.289744,0.000002321443,0.7092124,0.00004357867,0.0001090831,0.000662062,0.0001341067,0.000043323,0.00004910377],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2876921,"threshold_uncertainty_score":0.6662501,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1796252776","doi":"10.1002/nla.1977","title":"A generalized predictive analysis tool for multigrid methods","year":2015,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Multigrid method; Discretization; Mathematics; Applied mathematics; Computation; Diffusion; Class (philosophy); Convergence (economics); Partial differential equation; Mathematical optimization; Computer science; Mathematical analysis; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.03789095206775524,"gpt":0.364729005794814,"spread":0.3268380537270588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003164323,0.000231522,0.0004514468,0.0001443866,0.00008258287,0.00002407534,0.0002349245,0.00008368375,0.00001752536],"category_scores_gemma":[0.000310594,0.0001951824,0.000150737,0.001631656,0.00007705384,0.00009963757,0.00003327908,0.0001696006,0.00002769249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001061522,"about_ca_system_score_gemma":0.00004254052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001898914,"about_ca_topic_score_gemma":3.34778e-7,"domain_scores_codex":[0.9986449,0.00008196505,0.0004016206,0.0003368744,0.0002540298,0.0002805505],"domain_scores_gemma":[0.9978269,0.001112483,0.00009192293,0.000412857,0.0003123969,0.0002434481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005907904,0.0001059419,0.0001678264,0.00003982101,0.0006700626,4.103312e-7,0.0001368696,0.9521974,0.0001253391,0.01451573,0.0002858888,0.03169569],"study_design_scores_gemma":[0.0005244119,0.00009318098,0.0001497105,0.000003913281,0.000435774,0.000003495217,0.00003317799,0.9417392,0.0007181966,0.03147586,0.02455196,0.0002711292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005329447,0.0001461583,0.9971109,0.00009890518,0.00005481959,0.001031822,0.00007993812,0.0005905703,0.0003539681],"genre_scores_gemma":[0.01382357,0.000005622268,0.9826322,0.0001186828,0.0002152563,0.002975611,0.0001050874,0.00006657899,0.00005741825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03142456,"threshold_uncertainty_score":0.7959305,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141654299","doi":"10.1002/nla.318","title":"Consistency adjustments for pairwise comparison matrices","year":2002,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Mathematics; Consistency (knowledge bases); Rank (graph theory); Pairwise comparison; Transitive relation; Matrix (chemical analysis); Applied mathematics; Low-rank approximation; Linear least squares; Least-squares function approximation; Mathematical optimization; Linear model; Combinatorics; Discrete mathematics; Statistics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.0225620477831706,"gpt":0.2657795065740389,"spread":0.2432174587908683,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001116504,0.0001699121,0.000234485,0.00006742281,0.0003069714,0.00007810808,0.0006747645,0.00005817953,0.0001108681],"category_scores_gemma":[0.00001971769,0.0001356575,0.00008123914,0.0006559338,0.00007777636,0.0002086519,0.00007690641,0.0001228435,0.0004143953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002333974,"about_ca_system_score_gemma":0.00002244816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004142515,"about_ca_topic_score_gemma":5.116821e-7,"domain_scores_codex":[0.9986916,0.00003829801,0.0002994045,0.0004463313,0.0002207994,0.0003035629],"domain_scores_gemma":[0.9986995,0.0002458771,0.0001458141,0.0006103669,0.0001149004,0.0001835758],"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":[0.00002377623,0.001144559,0.0009131056,0.00007043934,0.00007882342,0.000002984412,0.0003122061,0.0003432607,0.00004498606,0.7635603,0.006065694,0.2274399],"study_design_scores_gemma":[0.00102084,0.0003916497,0.0003755413,0.00001678176,0.00006083898,0.00002438063,0.00005377181,0.6616463,0.0005210453,0.0138183,0.3215867,0.0004838395],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002851773,0.0005606443,0.9939626,0.001215749,0.00004832766,0.0008569739,0.00002265224,0.0003167596,0.002731043],"genre_scores_gemma":[0.3511192,0.00003448399,0.645355,0.0007130075,0.0002360195,0.001571119,0.0000280791,0.00002646005,0.0009165811],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.749742,"threshold_uncertainty_score":0.553195,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1976129499","doi":"10.1002/nla.715","title":"Numerical optimization for constrained image registration","year":2010,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Solver; Image registration; Augmented Lagrangian method; Discretization; Multigrid method; Constraint (computer-aided design); Focus (optics); Domain (mathematical analysis); Mathematical optimization; Image (mathematics); Computer science; Matching (statistics); Volume (thermodynamics); Algorithm; Mathematics; Artificial intelligence; Geometry; Partial differential equation","retraction":null,"screen_n_in":null,"score":{"opus":0.01219782384400975,"gpt":0.2882343383597085,"spread":0.2760365145156988,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000136191,0.0002400164,0.000268598,0.00006823832,0.0001626265,0.00004776046,0.0002247237,0.0001244327,0.0001172066],"category_scores_gemma":[0.000239917,0.0002195982,0.00007469601,0.0005538598,0.0001639555,0.0001784243,0.00001378712,0.0003519278,0.00004592704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003647861,"about_ca_system_score_gemma":0.00004766523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001064434,"about_ca_topic_score_gemma":4.46063e-7,"domain_scores_codex":[0.9987,0.00001950645,0.0004206622,0.0003284896,0.0002403735,0.0002910288],"domain_scores_gemma":[0.9983589,0.0007049537,0.0001138186,0.0003859229,0.000247316,0.000189081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004077049,0.0001926482,0.00002640538,0.0001439212,0.0000592502,0.000001103216,0.00005041584,0.8699276,0.004343827,0.0923444,0.0003949758,0.03247464],"study_design_scores_gemma":[0.000383739,0.00007794253,0.00003069625,0.000007698362,0.00003262957,0.00002579886,0.000015302,0.9694878,0.001626727,0.01721188,0.01079657,0.0003032281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002504167,0.00001309084,0.9951151,0.0003917826,0.0001089974,0.001077202,0.00004450436,0.0007139595,0.002284937],"genre_scores_gemma":[0.09777021,0.000003608755,0.9002548,0.0001098563,0.0003162925,0.001287237,0.0001452699,0.00008185962,0.00003091447],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09956016,"threshold_uncertainty_score":0.8954953,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2010972644","doi":"10.1002/nla.701","title":"A simultaneous decomposition of a matrix triplet with applications","year":2010,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Shanghai Municipal Education Commission; McGill University; Natural Science Foundation of Shanghai","keywords":"Hermitian matrix; Mathematics; Matrix (chemical analysis); Decomposition; Matrix function; Matrix decomposition; Pure mathematics; Applied mathematics; Algebra over a field; Symmetric matrix; Eigenvalues and eigenvectors; Physics; Quantum mechanics; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.004614076783061271,"gpt":0.2573955205973986,"spread":0.2527814438143373,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000149488,0.0002062164,0.0002639086,0.0001137965,0.0002363583,0.00006138114,0.0008562406,0.0000925264,0.00005800606],"category_scores_gemma":[0.00001639862,0.0001554706,0.00006501487,0.001285035,0.0001861253,0.0001955712,0.00008808041,0.0003486215,0.0001356552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001534859,"about_ca_system_score_gemma":0.0001201389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001427066,"about_ca_topic_score_gemma":0.000006465971,"domain_scores_codex":[0.9985169,0.00003969587,0.0003369738,0.0005045597,0.0003229394,0.0002789208],"domain_scores_gemma":[0.9979166,0.0003642488,0.0002287775,0.001026202,0.0002497781,0.0002144339],"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":[0.00009456636,0.0008307124,0.000194458,0.00005397792,0.00006389686,0.000007269944,0.0001500418,0.002103444,0.006344873,0.9328191,0.0000534225,0.05728429],"study_design_scores_gemma":[0.003538554,0.001583932,0.0006223873,0.00006037036,0.0002411013,0.00081602,0.0001082821,0.6058022,0.02525229,0.05357365,0.3066118,0.001789389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00317869,0.00002939705,0.9936545,0.0006671282,0.00002125707,0.001060288,0.00003505001,0.0002755975,0.001078074],"genre_scores_gemma":[0.5314837,0.000003086818,0.4672456,0.0001039185,0.0001203807,0.0008634891,0.00003314894,0.0000183972,0.0001282374],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8792454,"threshold_uncertainty_score":0.6339906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2121096325","doi":"10.1002/nla.567","title":"Efficiency‐based <i>h</i>‐ and <i>hp</i>‐refinement strategies for finite element methods","year":2008,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Dimension (graph theory); Finite element method; Grid; Work (physics); Mathematical optimization; Mathematics; Reduction (mathematics); Partial differential equation; Singularity; Applied mathematics; Computer science; Algorithm; Geometry; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.03086172452935074,"gpt":0.3294186889575105,"spread":0.2985569644281597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001821831,0.0002427167,0.0002962853,0.00007242045,0.0002264043,0.00002351268,0.0001724292,0.00005703048,0.00002132112],"category_scores_gemma":[0.00006956782,0.000206566,0.00005653202,0.0004840181,0.0001550387,0.00008148872,0.00002869822,0.0001613378,0.00001223138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004446477,"about_ca_system_score_gemma":0.00006459786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000129357,"about_ca_topic_score_gemma":2.892986e-7,"domain_scores_codex":[0.9987301,0.00004125678,0.0003817725,0.0003207239,0.0002239072,0.0003022072],"domain_scores_gemma":[0.9977956,0.001552737,0.00007827215,0.0002986083,0.0001212333,0.0001535291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000327837,0.0002298447,0.00005269874,0.0002291796,0.00006514586,0.000001489556,0.0001488062,0.904511,0.0007432157,0.04105252,0.0002147683,0.05271848],"study_design_scores_gemma":[0.0005698942,0.000190349,0.00006400896,0.0000149635,0.00004047378,0.00001124404,0.0000671727,0.9137015,0.002064189,0.02212395,0.06081458,0.000337706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003707664,0.0002159606,0.9971207,0.0001941938,0.00003614247,0.0009512929,0.00003488201,0.0003771318,0.0006988894],"genre_scores_gemma":[0.04957208,0.00002491543,0.9480747,0.0003088075,0.00008716404,0.001820749,0.00003508586,0.00005768304,0.00001881135],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06059981,"threshold_uncertainty_score":0.8423518,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056707245","doi":"10.1002/nla.258","title":"On the growth factor in Gaussian elimination for generalized Higham matrices","year":2002,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Gaussian elimination; Hermitian matrix; Mathematics; Positive-definite matrix; Matrix (chemical analysis); Gaussian; Combinatorics; Class (philosophy); Factor (programming language); Upper and lower bounds; Pure mathematics; Mathematical analysis; Physics; Computer science; Chemistry; Computational chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.01661374818348609,"gpt":0.2450198333137332,"spread":0.2284060851302471,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001304436,0.0001402384,0.0001388165,0.00009320819,0.0002081729,0.00008275318,0.0006317405,0.000051186,0.0001080955],"category_scores_gemma":[0.00004340618,0.00008679354,0.00005288446,0.0008296615,0.00004359499,0.0001588,0.00004146391,0.0001382628,0.0001454554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003017404,"about_ca_system_score_gemma":0.00001345031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008931739,"about_ca_topic_score_gemma":0.000001535676,"domain_scores_codex":[0.9989392,0.00006335395,0.0002091618,0.0003482011,0.0002063398,0.0002337486],"domain_scores_gemma":[0.9988487,0.0004702009,0.00009908132,0.0004350247,0.0000684281,0.00007855616],"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":[0.000009372258,0.0001612962,0.0000296172,0.000009124406,0.000007005121,5.728335e-7,0.0001235981,0.00009221931,0.00003405858,0.9865963,0.0004177438,0.01251913],"study_design_scores_gemma":[0.001472485,0.0004775569,0.002022283,0.0000276199,0.00002684389,0.00001248765,0.00003926734,0.8054506,0.002572912,0.149811,0.03747532,0.0006117366],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003305396,0.0000593501,0.9845487,0.009927425,0.00003338033,0.0009015914,0.00001836191,0.0001367137,0.001069051],"genre_scores_gemma":[0.8873215,0.00002574186,0.1093412,0.00109234,0.000171511,0.001608847,0.00001393901,0.00001985745,0.0004050274],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8840161,"threshold_uncertainty_score":0.3539338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3135361124","doi":"10.1002/nla.2367","title":"Optimizing multigrid reduction‐in‐time and Parareal coarse‐grid operators for linear advection","year":2021,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers; Australian Government; Lawrence Livermore National Laboratory; U.S. Department of Energy","keywords":"Multigrid method; Partial differential equation; Advection; Convergence (economics); Mathematics; Applied mathematics; Reduction (mathematics); Grid; Elliptic partial differential equation; Upwind scheme; Polygon mesh; Mathematical optimization; Hyperbolic partial differential equation; Computer science; Mathematical analysis; Geometry; Discretization","retraction":null,"screen_n_in":null,"score":{"opus":0.01548230655425855,"gpt":0.2866689558773092,"spread":0.2711866493230507,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001166529,0.0002123684,0.000310166,0.00007836874,0.000136031,0.00003229207,0.0001163736,0.0000939539,0.00002254941],"category_scores_gemma":[0.0001159639,0.0002076372,0.00005071115,0.0006902927,0.00007729865,0.0001425895,0.00003693689,0.0002483505,0.00002674565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008035599,"about_ca_system_score_gemma":0.00004194678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002477021,"about_ca_topic_score_gemma":8.624237e-7,"domain_scores_codex":[0.9987562,0.00003846837,0.0003771429,0.0003802266,0.0001851523,0.000262795],"domain_scores_gemma":[0.9989109,0.0004624197,0.00005867122,0.000253641,0.0001648303,0.0001495526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004534957,0.0002238094,0.0001070336,0.0001489497,0.00007049034,0.000003988819,0.0002135498,0.9659873,0.003315657,0.002857739,0.0001300896,0.02689607],"study_design_scores_gemma":[0.0006546399,0.00007299856,0.0001423311,0.00004675255,0.0000396812,0.00008145472,0.00008828777,0.9795169,0.00607438,0.003027405,0.009896004,0.0003591166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008005765,0.0002470657,0.9902425,0.0001947191,0.00009944667,0.0006811849,0.00005347564,0.0003076124,0.0001682095],"genre_scores_gemma":[0.02485298,0.00005971261,0.9735088,0.00006377329,0.0003715609,0.0008859891,0.0001200292,0.00007291359,0.00006421403],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02653695,"threshold_uncertainty_score":0.8467201,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1983085277","doi":"10.1002/nla.642","title":"A twisted factorization method for symmetric SVD of a complex symmetric tridiagonal matrix","year":2009,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Tridiagonal matrix; Orthogonality; Singular value decomposition; Mathematics; Matrix decomposition; QR decomposition; Singular value; Factorization; FLOPS; Matrix (chemical analysis); Divide and conquer algorithms; Symmetric matrix; Applied mathematics; Incomplete LU factorization; Algebra over a field; Algorithm; Pure mathematics; Computer science; Parallel computing; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.02501987492455005,"gpt":0.3326721764473136,"spread":0.3076523015227635,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003675653,0.0002064469,0.0003695081,0.0006139181,0.0001374298,0.00007510364,0.0007205276,0.0001132266,0.00001133749],"category_scores_gemma":[0.0001399926,0.0001792027,0.0001267785,0.00533415,0.00003976561,0.0002544404,0.00005100838,0.0001651184,0.00001656627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005977974,"about_ca_system_score_gemma":0.0001474642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001556463,"about_ca_topic_score_gemma":6.410773e-7,"domain_scores_codex":[0.9981656,0.0001087046,0.0005259154,0.0005053128,0.0004224335,0.0002720276],"domain_scores_gemma":[0.9977777,0.0005855852,0.0003635708,0.0006339325,0.0004826453,0.0001565616],"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":[0.00003029552,0.0004008771,0.00005833538,0.00001879589,0.00002635262,2.52232e-7,0.0001048437,0.0003370994,0.0014942,0.9176541,0.000388202,0.07948665],"study_design_scores_gemma":[0.001840412,0.001788198,0.008089424,0.00002196957,0.00009815367,0.00003205683,0.00002564922,0.8225228,0.01672161,0.07299253,0.0751299,0.0007372978],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001181573,0.00006731683,0.9953083,0.001753257,0.00001560311,0.001465855,0.00004139507,0.0004516525,0.000778486],"genre_scores_gemma":[0.3175755,0.000006228818,0.6813332,0.0004929311,0.00005470637,0.0003658329,0.00009566141,0.00001415849,0.00006174118],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8446615,"threshold_uncertainty_score":0.7307675,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111507332","doi":"10.1002/nla.1837","title":"Steepest descent preconditioning for nonlinear GMRES optimization","year":2012,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Lawrence Livermore National Laboratory; U.S. Department of Energy","keywords":"Generalized minimal residual method; Mathematics; Gradient descent; Method of steepest descent; Nonlinear conjugate gradient method; Mathematical optimization; Conjugate gradient method; Optimization problem; Line search; Convergence (economics); Nonlinear system; Applied mathematics; Iterative method; Computer science; Artificial neural network","retraction":null,"screen_n_in":null,"score":{"opus":0.04170620897805142,"gpt":0.3519899076566608,"spread":0.3102836986786093,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002465473,0.0002169655,0.0002536621,0.0001158223,0.000387119,0.00006541651,0.0002486619,0.0001043963,0.0002632299],"category_scores_gemma":[0.0003283153,0.0001895941,0.00007419108,0.0006316193,0.0001022513,0.0006456311,0.00005592491,0.0002099269,0.00006505623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001111208,"about_ca_system_score_gemma":0.00008018006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002050919,"about_ca_topic_score_gemma":0.000001132763,"domain_scores_codex":[0.9983109,0.00004920219,0.0003951069,0.0003471335,0.0003565834,0.0005411088],"domain_scores_gemma":[0.9979975,0.0005968343,0.0001969922,0.000460731,0.0004305022,0.0003174945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003097042,0.004054433,0.002777867,0.0004655597,0.0003391253,9.215976e-7,0.0007340983,0.5936372,0.0001235632,0.36541,0.002691627,0.02945586],"study_design_scores_gemma":[0.001966133,0.0002945102,0.0002828967,0.00005689518,0.0001689761,0.00003573628,0.0002959295,0.914285,0.002033533,0.00664195,0.0730895,0.0008489625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002956534,0.00006831001,0.9961181,0.0003816674,0.00003710671,0.001996339,0.0001167373,0.0002709435,0.0007151336],"genre_scores_gemma":[0.01178745,0.00002346845,0.9833593,0.0001375117,0.0005581589,0.002848346,0.0004822027,0.00009843528,0.0007051202],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3587681,"threshold_uncertainty_score":0.7731421,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2988137070","doi":"10.1002/nla.2297","title":"Nesterov acceleration of alternating least squares for canonical tensor decomposition: Momentum step size selection and restart mechanisms","year":2020,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Acceleration; Mathematics; Gradient descent; Nonlinear system; Conjugate gradient method; Robustness (evolution); Tensor (intrinsic definition); Nonlinear conjugate gradient method; Mathematical optimization; Line search; Applied mathematics; Algorithm; Rate of convergence; Computer science; Artificial intelligence; Geometry; Key (lock)","retraction":null,"screen_n_in":null,"score":{"opus":0.03470059674419496,"gpt":0.3201134359785043,"spread":0.2854128392343093,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009352371,0.0001973468,0.000312338,0.00004319149,0.0002858556,0.00005549329,0.0001609644,0.00008499203,0.0000605116],"category_scores_gemma":[0.00008398619,0.0001790603,0.00007333384,0.0003833723,0.00006323574,0.0001304994,0.00004013168,0.0001619084,0.00001100199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003854425,"about_ca_system_score_gemma":0.00005544324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001436178,"about_ca_topic_score_gemma":0.00001017751,"domain_scores_codex":[0.9985548,0.00004590875,0.00050351,0.0004360024,0.0002455941,0.0002142285],"domain_scores_gemma":[0.9984966,0.0005298567,0.0002810334,0.000220636,0.0002859106,0.0001859704],"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":[0.0004849272,0.0009270637,0.0008486314,0.000420594,0.0001877257,0.000001067948,0.0004932304,0.0007946434,0.07734317,0.9106843,0.001628053,0.006186598],"study_design_scores_gemma":[0.008351467,0.003781817,0.006013777,0.0002176486,0.0009811107,0.0001832788,0.001231943,0.7011079,0.07738822,0.1683782,0.03034116,0.0020235],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07140324,0.00001246934,0.9209508,0.005669602,0.00001216917,0.001558197,0.00008107878,0.0001851406,0.0001273428],"genre_scores_gemma":[0.6196093,0.000004266674,0.378618,0.0004116514,0.0001424894,0.001078394,0.00006400765,0.00003547889,0.00003643614],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7423061,"threshold_uncertainty_score":0.7301867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2336877474","doi":"10.1002/nla.2047","title":"Preconditioning a mass‐conserving discontinuous Galerkin discretization of the Stokes equations","year":2016,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Preconditioner; Multigrid method; Discretization; Mathematics; Saddle point; Discontinuous Galerkin method; Finite element method; Applied mathematics; Navier–Stokes equations; Linear system; Galerkin method; Saddle; Relaxation (psychology); Block (permutation group theory); Mathematical analysis; Mathematical optimization; Compressibility; Partial differential equation; Geometry; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01127663032184782,"gpt":0.2477752979146314,"spread":0.2364986675927836,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009620425,0.0001616275,0.000203535,0.000053418,0.0001446684,0.00001535376,0.000280747,0.00005136751,0.00005748054],"category_scores_gemma":[0.0002419882,0.00009377523,0.00006967812,0.000625507,0.0001701756,0.0001577109,0.00003801132,0.0001237136,0.00002903375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006058536,"about_ca_system_score_gemma":0.00003204355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001421503,"about_ca_topic_score_gemma":0.00000126745,"domain_scores_codex":[0.9988979,0.00005805972,0.0003938503,0.0002009085,0.0002562158,0.0001930403],"domain_scores_gemma":[0.9981496,0.001088854,0.0001587883,0.0004065711,0.000122932,0.00007319948],"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":[0.00002808554,0.0002449943,0.00458603,0.0002705575,0.0002346184,5.792928e-7,0.0003713646,0.3884999,0.02473424,0.4841528,0.000180294,0.09669644],"study_design_scores_gemma":[0.001552851,0.0001822155,0.01548309,0.0008251647,0.0002892012,0.00003225352,0.0002724971,0.5798756,0.03119323,0.360018,0.008955019,0.00132094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002862033,0.00005090224,0.9944156,0.0005865361,0.00005340543,0.0005212525,0.00006391227,0.0002191153,0.00122718],"genre_scores_gemma":[0.6240941,0.000006660455,0.3752613,0.00003478496,0.00007133715,0.0003925243,0.00001087655,0.00003960597,0.00008876882],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6212321,"threshold_uncertainty_score":0.3824043,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992234740","doi":"10.1002/nla.782","title":"Parallel numerical solution of the time‐harmonic Maxwell equations in mixed form","year":2011,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Multigrid method; Discretization; Mathematics; Curl (programming language); Solver; Finite element method; Preconditioner; Maxwell's equations; Polygon mesh; Iterative method; Applied mathematics; Electromagnetic field solver; Mathematical analysis; Partial differential equation; Algorithm; Geometry; Computer science; Mathematical optimization; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.03025319188831007,"gpt":0.266435190812476,"spread":0.2361819989241659,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001451052,0.0002086658,0.0003027933,0.00008539073,0.00008987908,0.000006618088,0.0004057947,0.00009221591,0.00009043067],"category_scores_gemma":[0.0001144468,0.0001573683,0.0000943523,0.001204381,0.0001467357,0.0001138165,0.00007144918,0.0003207072,0.0001102767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009896563,"about_ca_system_score_gemma":0.00004544298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000103006,"about_ca_topic_score_gemma":0.000001686469,"domain_scores_codex":[0.998557,0.00006390029,0.0005369535,0.0002459606,0.0002966831,0.0002995557],"domain_scores_gemma":[0.9986668,0.0005100722,0.0001427254,0.0004814989,0.00009650366,0.0001024522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002256674,0.002864631,0.003184434,0.0005039148,0.0003824036,0.000005532881,0.002409319,0.5307047,0.00519775,0.3291472,0.0006250899,0.1247494],"study_design_scores_gemma":[0.0004805518,0.0000911713,0.005801845,0.00004190193,0.00005336115,0.00001043834,0.00004286409,0.8925031,0.002304863,0.09662416,0.001693208,0.0003524732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001601731,0.00006808249,0.9950101,0.0001410692,0.0000473978,0.0007083233,0.00001799046,0.0001848641,0.002220459],"genre_scores_gemma":[0.4626088,0.000006225084,0.5367922,0.00004643229,0.00003426769,0.0004175624,0.0000178446,0.00004032839,0.00003624521],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4610071,"threshold_uncertainty_score":0.6417294,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2806424598","doi":"10.1002/nla.2147","title":"Local Fourier analysis of block‐structured multigrid relaxation schemes for the Stokes equations","year":2018,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Discretization; Relaxation (psychology); Mathematics; Block (permutation group theory); Convergence (economics); Applied mathematics; Saddle point; Fourier transform; Saddle; Finite element method; Mathematical optimization; Algorithm; Partial differential equation; Mathematical analysis; Geometry; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01966037727123458,"gpt":0.3040190220013343,"spread":0.2843586447300997,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001450969,0.0001717809,0.0002975698,0.0001414043,0.0002161588,0.00001471798,0.0002558647,0.00007219613,0.00004002816],"category_scores_gemma":[0.0002862094,0.0001208778,0.0001273171,0.001837621,0.000331294,0.00007355287,0.00002620855,0.0001458865,0.00001302683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004718754,"about_ca_system_score_gemma":0.00002844653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003292195,"about_ca_topic_score_gemma":0.000005320914,"domain_scores_codex":[0.998855,0.00002708128,0.0004163071,0.0002269366,0.0002768368,0.0001978137],"domain_scores_gemma":[0.996681,0.00222857,0.000164481,0.000454486,0.0003921055,0.00007939823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000363125,0.0000864599,0.000130964,0.00005162676,0.001133198,8.153981e-8,0.0002535584,0.8573571,0.0005098738,0.05597107,0.0001065553,0.08436316],"study_design_scores_gemma":[0.0001887312,0.00006276621,0.0005852464,0.000006596396,0.000646755,9.462665e-7,0.00007032022,0.976424,0.00215559,0.007501668,0.01220417,0.0001532047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001197868,0.0001024956,0.9973372,0.0002044099,0.00004951309,0.0007335054,0.00008230109,0.0001797865,0.0001128923],"genre_scores_gemma":[0.4565794,0.000004419084,0.5426867,0.0000459204,0.0001138248,0.0004899792,0.00004028894,0.00002610664,0.00001332925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4553816,"threshold_uncertainty_score":0.4929252,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2963626304","doi":"10.1002/nla.1963","title":"A nonlinearly preconditioned conjugate gradient algorithm for rank‐<i>R</i> canonical tensor approximation","year":2014,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Laboratory Directed Research and Development; Natural Sciences and Engineering Research Council of Canada; Lawrence Livermore National Laboratory; U.S. Department of Energy","keywords":"Preconditioner; Conjugate gradient method; Convergence (economics); Mathematics; Rank (graph theory); Tensor (intrinsic definition); Acceleration; Nonlinear conjugate gradient method; Nonlinear system; Algorithm; Applied mathematics; Mathematical optimization; Computer science; Iterative method; Pure mathematics; Gradient descent; Combinatorics; Artificial intelligence; Artificial neural network","retraction":null,"screen_n_in":null,"score":{"opus":0.01939508976469891,"gpt":0.2887760599794227,"spread":0.2693809702147238,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002754039,0.0003179672,0.000454928,0.0001078804,0.0004860301,0.0000792795,0.0003293302,0.0001492975,0.0001133532],"category_scores_gemma":[0.00009527326,0.0002699438,0.0001799606,0.0005243391,0.000173977,0.0001427108,0.00003612998,0.0002542034,0.0002171141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007521245,"about_ca_system_score_gemma":0.00008286454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001202853,"about_ca_topic_score_gemma":0.000007916099,"domain_scores_codex":[0.9978486,0.00008082278,0.0006493522,0.0006505525,0.0003310874,0.0004396167],"domain_scores_gemma":[0.9974237,0.0007732444,0.0003170988,0.0007256651,0.0004347567,0.0003255447],"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":[0.0001329687,0.002847971,0.0001068172,0.0001541936,0.0002204317,7.929349e-7,0.000225508,0.0001709805,0.001223535,0.9156867,0.006253873,0.07297618],"study_design_scores_gemma":[0.005686503,0.001000237,0.0006781157,0.00006603466,0.0005244989,0.0001116227,0.0001226045,0.4176864,0.004258652,0.2274836,0.3410499,0.001331796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003543493,0.00001287997,0.9888576,0.002449051,0.00003648563,0.002939911,0.0004105985,0.0005051383,0.001244841],"genre_scores_gemma":[0.09040556,0.000005400363,0.8969364,0.001060035,0.0005748688,0.009291874,0.0009602787,0.0001085816,0.000656991],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6882032,"threshold_uncertainty_score":0.9999753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3006898615","doi":"10.1002/nla.2285","title":"Two‐level Fourier analysis of multigrid for higher‐order finite‐element discretizations of the Laplacian","year":2020,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Smoothing; Finite element method; Applied mathematics; Relaxation (psychology); Mathematics; Grid; Convergence (economics); Mathematical optimization; Laplace operator; Fourier analysis; Fourier transform; Partial differential equation; Computer science; Algorithm; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.03753276415587457,"gpt":0.3065091364014927,"spread":0.2689763722456182,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006384995,0.0001536449,0.0003627604,0.00006730784,0.00007611507,0.000006332825,0.0002918782,0.00004067443,0.00006322983],"category_scores_gemma":[0.0002181203,0.0001114487,0.0001485151,0.002524953,0.0001180444,0.00004248932,0.00004843913,0.0001206859,0.000003800439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000228103,"about_ca_system_score_gemma":0.00002908287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002470284,"about_ca_topic_score_gemma":0.000001828848,"domain_scores_codex":[0.998871,0.00003037169,0.0004748551,0.0002022832,0.0002654165,0.0001561008],"domain_scores_gemma":[0.9981952,0.0009278907,0.0001771529,0.0003442627,0.000254177,0.0001013603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001344134,0.00007938621,0.0005445429,0.00008460764,0.0004393392,4.116773e-8,0.0001392044,0.9597934,0.0002113643,0.03471054,0.00004768409,0.003936416],"study_design_scores_gemma":[0.0003211862,0.0000564188,0.001127386,0.00001132869,0.0005346171,1.558876e-7,0.0000407149,0.9856706,0.001092089,0.004425748,0.006567805,0.0001520102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003531947,0.00003336043,0.9970983,0.0008799544,0.00002607565,0.0007120934,0.000533591,0.00007967356,0.0002837643],"genre_scores_gemma":[0.2424702,0.000003591141,0.7567598,0.0001731101,0.00006199897,0.0003978407,0.00008310694,0.00003190587,0.00001848788],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.242117,"threshold_uncertainty_score":0.4544748,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1840032205","doi":"10.1002/nla.1823","title":"On condition numbers for Moore–Penrose inverse and linear least squares problem involving Kronecker products","year":2012,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Kronecker product; Mathematics; Kronecker delta; Combinatorics; Moore–Penrose pseudoinverse; Inverse; Rank (graph theory); Linear least squares; Least-squares function approximation; Product (mathematics); Condition number; Applied mathematics; Upper and lower bounds; Matrix (chemical analysis); Linear model; Statistics; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01265069169889564,"gpt":0.2548747174177887,"spread":0.242224025718893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002840122,0.0002096917,0.0001986498,0.00007839806,0.0003354203,0.00007380381,0.0003195212,0.00007583786,0.00002445081],"category_scores_gemma":[0.00005327534,0.0001706562,0.00004163766,0.0005284875,0.000135102,0.0005492612,0.00009370284,0.0001902481,0.0001709262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000342579,"about_ca_system_score_gemma":0.00005852814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008707094,"about_ca_topic_score_gemma":0.000001501451,"domain_scores_codex":[0.9985836,0.00005546886,0.0002399939,0.0004947847,0.0002232711,0.0004029274],"domain_scores_gemma":[0.9987534,0.0002086766,0.0001345878,0.0005004554,0.0001446651,0.0002582587],"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":[0.00007128906,0.0006876302,0.001039896,0.0001468724,0.00005047938,0.000001024908,0.0009125687,0.0005707205,0.0006301033,0.9773323,0.001642078,0.01691501],"study_design_scores_gemma":[0.006366896,0.002467549,0.005364697,0.0003064541,0.000296179,0.0002236158,0.0007537159,0.455634,0.02330247,0.1455221,0.3562281,0.003534274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0136059,0.0001248629,0.9820059,0.00178997,0.00007014475,0.001598229,0.00003908225,0.0002164166,0.0005494903],"genre_scores_gemma":[0.5435082,0.000009274037,0.4537874,0.0006559793,0.0004604536,0.001122969,0.00009648554,0.00003407266,0.0003252162],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8318102,"threshold_uncertainty_score":0.6959158,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1636009176","doi":"10.1002/nla.800","title":"Fast multilevel methods for Markov chains","year":2011,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Israel Science Foundation","keywords":"Markov chain; Speedup; Residual; Mathematics; Algorithm; Iterative method; Markov process; Applied mathematics; Markov model; Computer science; Mathematical optimization; Parallel computing; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02959064902754927,"gpt":0.3115063589447691,"spread":0.2819157099172198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003254385,0.0001737121,0.0002023576,0.00006799194,0.0002346098,0.00003788281,0.0008628967,0.00006799283,0.00007006455],"category_scores_gemma":[0.00003482798,0.0001360473,0.00008627922,0.000476357,0.00008533807,0.0001796927,0.0001233239,0.0001414685,0.0001034344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001725861,"about_ca_system_score_gemma":0.00005691475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000101329,"about_ca_topic_score_gemma":4.781751e-7,"domain_scores_codex":[0.9987618,0.00007633385,0.0002357494,0.0004867673,0.0001180725,0.0003212409],"domain_scores_gemma":[0.9985648,0.0002659624,0.0001066236,0.0007314705,0.0001309546,0.000200122],"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":[0.00001809201,0.0001787964,0.00002481636,0.00001207061,0.0000223752,5.230735e-7,0.0002742282,0.00001093284,0.00009875528,0.5249048,0.00007646762,0.4743781],"study_design_scores_gemma":[0.001003808,0.0003840113,0.0009951349,0.00001396178,0.0000488741,0.00003905382,0.00006487803,0.7733704,0.008127021,0.07050986,0.1447357,0.0007073434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003415907,0.0000395741,0.9953755,0.0003174385,0.00005513601,0.0007919045,0.0000189039,0.0002862525,0.003081153],"genre_scores_gemma":[0.01326299,0.000003504237,0.9839541,0.000410451,0.0001429696,0.001391351,0.00001290643,0.00002230573,0.0007994059],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7733594,"threshold_uncertainty_score":0.5547849,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113559515","doi":"10.1002/nla.757","title":"An efficient hierarchical preconditioner for quadratic discretizations of finite element problems","year":2010,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Preconditioner; Multigrid method; Krylov subspace; Finite element method; Discretization; Solver; Mathematics; Applied mathematics; Mathematical optimization; Robustness (evolution); Iterative method; Linear system; Polygon mesh; Computer science; Quadratic equation; Algorithm; Partial differential equation; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.01151573169547392,"gpt":0.2890850281962522,"spread":0.2775692965007783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001366575,0.000179427,0.0002478578,0.00008453638,0.0001261753,0.00001852714,0.0002320236,0.00007305757,0.00007617597],"category_scores_gemma":[0.0001174834,0.0001509441,0.0000605596,0.0004840223,0.00015294,0.00009001957,0.00001749793,0.0002612528,0.0000156231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002152326,"about_ca_system_score_gemma":0.000036391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.252484e-7,"about_ca_topic_score_gemma":0.000001671977,"domain_scores_codex":[0.9987853,0.00002694375,0.0004652182,0.0002611401,0.000233218,0.0002282191],"domain_scores_gemma":[0.998243,0.0008765113,0.0001073639,0.0004130918,0.000185154,0.0001748382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007924898,0.0003071057,0.00005564941,0.00012071,0.00003011402,6.732026e-8,0.0001112942,0.8713083,0.001935362,0.121896,0.00001469491,0.004212759],"study_design_scores_gemma":[0.000262043,0.000145335,0.0001999555,0.00001478775,0.00003760569,0.000003173954,0.00002176348,0.9438078,0.001345684,0.05115677,0.002802476,0.0002026277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004094614,0.0000122461,0.9936982,0.0001431355,0.00005654667,0.001331916,0.0001550468,0.0002473175,0.0002609601],"genre_scores_gemma":[0.3914163,0.000001322798,0.6066944,0.00002800655,0.00009086659,0.001569028,0.00015066,0.0000409464,0.00000845007],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3873217,"threshold_uncertainty_score":0.6155323,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2018978449","doi":"10.1002/nla.640","title":"Backward perturbation analysis for scaled total least‐squares problems","year":2009,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Ordinary least squares; Mathematics; Perturbation (astronomy); Upper and lower bounds; Least-squares function approximation; Applied mathematics; Mathematical optimization; Statistics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.02843203753759685,"gpt":0.302662501843118,"spread":0.2742304643055211,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001361037,0.0002790237,0.0005328856,0.0001331258,0.0002567897,0.0000573105,0.0002270248,0.000115348,0.0002112235],"category_scores_gemma":[0.0002095654,0.0002043482,0.0002497164,0.001590136,0.0001045979,0.0001026411,0.00002245373,0.0001942985,0.00009011844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005065145,"about_ca_system_score_gemma":0.00004016497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009526064,"about_ca_topic_score_gemma":0.000002670107,"domain_scores_codex":[0.9980757,0.0000429418,0.0004956419,0.0005640023,0.0003953582,0.0004263937],"domain_scores_gemma":[0.9980422,0.0007538701,0.0001758582,0.0004484971,0.000288266,0.0002912874],"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":[0.000486408,0.003424873,0.001551392,0.0001997103,0.001201957,0.000003858985,0.0004659641,0.002545791,0.0004526159,0.823788,0.003044038,0.1628354],"study_design_scores_gemma":[0.00207102,0.001846038,0.0140081,0.00003740807,0.00227307,0.00002512602,0.0001122488,0.2932837,0.000475204,0.6630819,0.02156764,0.001218528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002683715,0.00004896055,0.992395,0.002241573,0.00001657091,0.00134483,0.0001377829,0.0002710067,0.0008604972],"genre_scores_gemma":[0.4392954,0.000005538763,0.556945,0.0004348287,0.0003304443,0.001308579,0.0003009287,0.00004103092,0.001338243],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4366117,"threshold_uncertainty_score":0.8333076,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163749311","doi":"10.1002/nla.811","title":"A Markov‐modulated fluid flow queueing model under <i>D</i>‐policy","year":2011,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Idle; Markov chain; Queueing theory; Markov process; Fluid queue; Mathematical optimization; Mathematics; Flow (mathematics); Computer science; Applied mathematics; Statistics; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.01708096428007033,"gpt":0.235374970001567,"spread":0.2182940057214967,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001584591,0.0002838482,0.0002960097,0.0002782006,0.0003478879,0.00007014702,0.0004100765,0.00009291711,0.0003127216],"category_scores_gemma":[0.00007628465,0.000243951,0.0001047453,0.002122274,0.0001153065,0.0006561439,0.000149356,0.000226168,0.0007085124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005624711,"about_ca_system_score_gemma":0.00006497523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002851071,"about_ca_topic_score_gemma":0.00002227208,"domain_scores_codex":[0.998431,0.00001514114,0.0003472537,0.0005267732,0.0002559763,0.0004238017],"domain_scores_gemma":[0.9987833,0.0000549152,0.0002049536,0.0006681451,0.0002325149,0.0000561801],"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":[0.0002693478,0.00065066,0.0006603024,0.00008741179,0.0002739322,0.000007041423,0.0001572432,0.2241178,0.001385931,0.7602891,0.0009150389,0.01118619],"study_design_scores_gemma":[0.0003295503,0.00001083842,0.0003098279,0.00001556929,0.0001633232,0.000003256994,0.00005029569,0.8980036,0.0001197379,0.08841357,0.01218366,0.0003968084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007383408,0.0000293686,0.9677684,0.0008619266,0.00001796169,0.0004719717,0.00001013408,0.0006268162,0.02283004],"genre_scores_gemma":[0.9169233,0.000004385603,0.0769925,0.004073296,0.0007156293,0.000375908,0.0001371221,0.00009624742,0.000681633],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9095399,"threshold_uncertainty_score":0.9948034,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2338260032","doi":"10.1002/nla.2050","title":"Towards an optimal condition number of certain augmented Lagrangian‐type saddle‐point matrices","year":2016,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Invertible matrix; Saddle point; Eigenvalues and eigenvectors; Augmented Lagrangian method; Rank (graph theory); Block (permutation group theory); Matrix (chemical analysis); Saddle; Applied mathematics; Type (biology); Singular value decomposition; Combinatorics; Block matrix; Lagrangian; Singular value; Pure mathematics; Mathematical optimization; Algorithm; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.009549939276433841,"gpt":0.2723625157209429,"spread":0.2628125764445091,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002018209,0.0001740152,0.0002241594,0.00006873751,0.0001253667,0.00004113958,0.0006607287,0.00007494752,0.0005204446],"category_scores_gemma":[0.00002729364,0.0001122722,0.00006340536,0.0007843094,0.0001303919,0.0004722193,0.00009674564,0.00009792807,0.0003900634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000321735,"about_ca_system_score_gemma":0.00008966559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002148269,"about_ca_topic_score_gemma":7.44764e-7,"domain_scores_codex":[0.9985924,0.00009122934,0.0003157672,0.0004318551,0.0003015595,0.0002671451],"domain_scores_gemma":[0.9985677,0.0001645743,0.0001861978,0.0006589258,0.0002222832,0.0002003244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001908121,0.000931918,0.000696104,0.0000543867,0.0001079647,0.000007827032,0.0003172405,0.0002186481,0.003491339,0.7943698,0.0004050744,0.1992089],"study_design_scores_gemma":[0.01280144,0.005930683,0.01613641,0.0005732731,0.0006043768,0.0008399537,0.0007818323,0.2628648,0.1805145,0.2170647,0.2961761,0.00571191],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01496748,0.00003197958,0.9820624,0.001051217,0.0000482675,0.0003487332,0.00004470904,0.0002194023,0.001225812],"genre_scores_gemma":[0.7118313,0.00001850373,0.2873296,0.0001576046,0.0001560137,0.0001727679,0.00004465592,0.00002152626,0.0002680106],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6968638,"threshold_uncertainty_score":0.5698504,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013095747","doi":"10.1002/nla.242","title":"A divide and conquer approach to computing the mean first passage matrix for Markov chains via Perron complement reductions","year":2001,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Mathematics; Markov chain; FLOPS; Block matrix; Partition (number theory); Matrix multiplication; Combinatorics; Ergodic theory; Complement (music); Matrix (chemical analysis); Divide and conquer algorithms; Diagonal; Discrete mathematics; Computation; Algorithm; Parallel computing; Computer science; Pure mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01515081388627167,"gpt":0.2651078357017424,"spread":0.2499570218154707,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003876906,0.0002002266,0.0002124226,0.00006656005,0.001006433,0.0001375854,0.0006427698,0.00004251954,0.00001381939],"category_scores_gemma":[0.00001641029,0.0001395899,0.0000612966,0.0007133142,0.0001225949,0.0001152357,0.0002366975,0.0001698721,0.00002480541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003862103,"about_ca_system_score_gemma":0.00003142381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003151655,"about_ca_topic_score_gemma":0.000007996586,"domain_scores_codex":[0.9984779,0.00006634722,0.0002898941,0.0005599739,0.0002262556,0.0003796506],"domain_scores_gemma":[0.9986157,0.0002949512,0.000107597,0.0006568392,0.0001057603,0.0002191774],"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":[0.00005371554,0.0006216253,0.0003358663,0.00006234043,0.0001047961,0.000001486455,0.002385304,0.004782037,0.00008777186,0.9142891,0.002162609,0.07511333],"study_design_scores_gemma":[0.0006676567,0.0002231466,0.0008331876,0.00001716592,0.00005437699,0.0001456863,0.0002713274,0.6974167,0.00006346448,0.009246784,0.290626,0.000434514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007608566,0.00005800179,0.9861799,0.01010656,0.00003832998,0.001778757,0.0000262613,0.000179528,0.0008718287],"genre_scores_gemma":[0.6006911,0.000008741616,0.3966159,0.0006924339,0.0003600729,0.001147492,0.00003903499,0.00002373757,0.0004214845],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9050424,"threshold_uncertainty_score":0.7740773,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2146675507","doi":"10.1002/nla.1999","title":"A cyclic algorithm for maximum likelihood estimation using Schur complement","year":2015,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Centre interuniversitaire de recherche sur les reseaux d'entreprise, la logistique et le transport","keywords":"Hessian matrix; Schur complement; Coordinate descent; Mathematics; Complement (music); Algorithm; Mathematical optimization; Matrix (chemical analysis); Block (permutation group theory); Schur decomposition; System of linear equations; Hessian equation; Transformation (genetics); Applied mathematics; Linear system; Descent (aeronautics); Eigenvalues and eigenvectors; Partial differential equation","retraction":null,"screen_n_in":null,"score":{"opus":0.02318148606959327,"gpt":0.2715561412659055,"spread":0.2483746551963122,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001135293,0.0001517381,0.0001507733,0.00009284569,0.00009249099,0.00003562509,0.0001420568,0.0000511775,0.000008653998],"category_scores_gemma":[0.00000705773,0.0001430383,0.00004063653,0.0003285204,0.00003077326,0.0001165222,0.00002657064,0.0000985077,0.0000424822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001036572,"about_ca_system_score_gemma":0.00002880838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001056393,"about_ca_topic_score_gemma":0.000001896241,"domain_scores_codex":[0.999125,0.00001143555,0.0002313567,0.0002056756,0.000184205,0.0002423482],"domain_scores_gemma":[0.9994124,0.00002599966,0.00004353064,0.0002502633,0.00008727189,0.0001805074],"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":[0.00001184653,0.00017913,0.00002526561,0.00005058692,0.00009696132,8.820738e-7,0.00007453291,0.0555977,0.0001417603,0.004445245,0.0147014,0.9246747],"study_design_scores_gemma":[0.0004520953,0.00006465995,0.0000242742,0.000009110931,0.0000434725,0.000005656838,0.00003443484,0.8601547,0.0002658618,0.001173337,0.1376196,0.000152844],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00020072,0.0000495494,0.994582,0.0001675193,0.00005194277,0.001224844,0.00005329261,0.003101541,0.0005685643],"genre_scores_gemma":[0.1496301,0.000007182986,0.8484943,0.0001399634,0.0001360923,0.001349123,0.0001876767,0.00004506001,0.00001053791],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9245219,"threshold_uncertainty_score":0.5832931,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108510172","doi":"10.1002/nla.1995","title":"Spectral recycling strategies for the solution of nonlinear eigenproblems in thermoacoustics","year":2015,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Krylov subspace; Solver; Nonlinear system; Generalized minimal residual method; Eigenvalues and eigenvectors; Block (permutation group theory); Chebyshev filter; Arnoldi iteration; Mathematics; Stability (learning theory); Computer science; Applied mathematics; Integrator; Mathematical optimization; Iterative method; Algorithm; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.01994205781747695,"gpt":0.2485625784271067,"spread":0.2286205206096297,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001354828,0.0001054013,0.0001373419,0.00004580526,0.00004615173,0.00001811843,0.000152452,0.00005726066,0.000006118469],"category_scores_gemma":[0.00001731775,0.00007723008,0.00003768214,0.0003817632,0.00006694923,0.00005758777,0.0000125961,0.0001636172,0.000008276928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004914467,"about_ca_system_score_gemma":0.00007112605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002483551,"about_ca_topic_score_gemma":0.000048549,"domain_scores_codex":[0.9993291,0.000009287093,0.0002437846,0.0001210243,0.0001212726,0.0001755295],"domain_scores_gemma":[0.9994522,0.0001239982,0.00004423757,0.0002228163,0.00009578807,0.0000609647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003657582,0.0000852808,0.000262273,0.00004282753,0.00003032546,2.430004e-7,0.0003087036,0.9752405,0.0006253529,0.01494847,0.0001592349,0.008260175],"study_design_scores_gemma":[0.0003373461,0.00005211423,0.0003017031,0.000009362933,0.00002447522,0.000002431786,0.0004388358,0.9918647,0.0001228119,0.002695144,0.004044055,0.0001070181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00764129,0.0001741388,0.9905128,0.0001816906,0.00004789112,0.0005915583,0.00003861033,0.000116479,0.0006955657],"genre_scores_gemma":[0.9263999,0.00004043036,0.07297503,0.0000275735,0.0001210992,0.0003156822,0.00006025088,0.00003241458,0.00002763857],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9187586,"threshold_uncertainty_score":0.3149351,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2166356498","doi":"10.1002/nla.787","title":"On the perturbation of the Q‐factor of the QR factorization","year":2011,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Perturbation (astronomy); Mathematics; Invertible matrix; Factorization; Applied mathematics; Combinatorics; Pure mathematics; Algorithm; Physics; Quantum mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.01687156204401739,"gpt":0.2127217399330281,"spread":0.1958501778890108,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102277,0.00008922376,0.00009314105,0.00001858464,0.0001852684,0.00001163681,0.001034355,0.00003765689,0.00006347882],"category_scores_gemma":[0.00006422613,0.00003619567,0.00007096538,0.0007303793,0.0001391624,0.00007719571,0.0001071746,0.0001362877,0.00001498662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001189378,"about_ca_system_score_gemma":0.00005181922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001160343,"about_ca_topic_score_gemma":6.787318e-7,"domain_scores_codex":[0.9991726,0.0001005979,0.0001910436,0.0001685408,0.0002680788,0.00009911849],"domain_scores_gemma":[0.9985486,0.0002289832,0.0002213153,0.0008605099,0.0001109697,0.00002960198],"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":[0.00000667354,0.0001070035,0.0005306771,0.000005673146,0.00001172144,1.776771e-8,0.00059157,0.00004956661,0.0003990748,0.995233,0.00003416812,0.003030831],"study_design_scores_gemma":[0.0008477228,0.0005835417,0.126029,0.000116199,0.0001050024,0.00001229269,0.0002240287,0.0964414,0.2708145,0.4907951,0.01336163,0.0006695416],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01347232,0.00001051597,0.9824405,0.001241182,0.00007834666,0.0005869971,0.00001543295,0.00003596675,0.002118764],"genre_scores_gemma":[0.9939947,0.000001390914,0.005437082,0.000237392,0.00003711127,0.00008249196,0.000001355895,0.000006906141,0.000201598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9805223,"threshold_uncertainty_score":0.1922107,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3092221604","doi":"10.1002/nla.2337","title":"Minimizing convex quadratics with variable precision conjugate gradients","year":2020,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Agence Nationale de la Recherche","keywords":"Mathematics; Conjugate gradient method; Context (archaeology); Computation; Conjugate; Quadratic equation; Matrix (chemical analysis); Mathematical optimization; Regular polygon; Variable (mathematics); Convex optimization; Applied mathematics; Algorithm; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.04017474802119845,"gpt":0.3171565609560845,"spread":0.2769818129348861,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001335431,0.0002733584,0.0004017488,0.00006590605,0.0002809704,0.00007033332,0.0003841364,0.00009717705,0.0002921534],"category_scores_gemma":[0.0003227101,0.0002063743,0.00004179769,0.001394032,0.0001792374,0.0002063472,0.0001017081,0.0004018836,0.0002214657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000556183,"about_ca_system_score_gemma":0.0001641567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005036683,"about_ca_topic_score_gemma":0.00000117902,"domain_scores_codex":[0.9978305,0.0000741492,0.000446742,0.0005774131,0.0006406161,0.0004306002],"domain_scores_gemma":[0.9977249,0.0005869236,0.0002194241,0.0005374837,0.000443676,0.0004875732],"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":[0.002871284,0.00428339,0.00416737,0.001241353,0.001196208,0.00008678935,0.005614576,0.1091049,0.002021238,0.817503,0.01094401,0.04096587],"study_design_scores_gemma":[0.004121319,0.001367246,0.00009601033,0.0001217159,0.0002240395,0.00005444948,0.0006563241,0.8558584,0.002668119,0.0267708,0.1068643,0.001197341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007233549,0.00002722012,0.993748,0.001547651,0.00001204942,0.001403245,0.0000431618,0.0003148106,0.002180519],"genre_scores_gemma":[0.03025032,0.00001696004,0.9676313,0.0007257492,0.0001546126,0.0006496324,0.00008699677,0.0001045545,0.0003798315],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7907322,"threshold_uncertainty_score":0.8415699,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2170774163","doi":"10.1002/nla.1825","title":"Hermitian‐type generalized singular value decomposition with applications","year":2012,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Shanghai Municipal Education Commission; National Natural Science Foundation of China; McGill University; Natural Science Foundation of Shanghai","keywords":"Hermitian matrix; Mathematics; Hermitian function; Singular value decomposition; Matrix (chemical analysis); Matrix function; Rank (graph theory); Pure mathematics; Algebra over a field; Applied mathematics; Symmetric matrix; Mathematical analysis; Combinatorics; Algorithm; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.009507974454374934,"gpt":0.2641563078538695,"spread":0.2546483333994945,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002146915,0.0002594363,0.0002583571,0.00009372675,0.0004585598,0.000107225,0.0006907805,0.00009017427,0.00006369594],"category_scores_gemma":[0.000006598801,0.0002008599,0.00006288099,0.001424311,0.0001269966,0.00049255,0.0001033775,0.0002323396,0.0004685532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005401822,"about_ca_system_score_gemma":0.00009408587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001451976,"about_ca_topic_score_gemma":6.331073e-7,"domain_scores_codex":[0.9982426,0.0001028163,0.0002940314,0.0005047872,0.0003542848,0.0005015443],"domain_scores_gemma":[0.9981669,0.0001181055,0.0001612875,0.000979836,0.0001861858,0.0003876871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003828603,0.0005794837,0.0005090151,0.0000209191,0.00006380944,0.000002175019,0.0001365294,0.0008543854,0.0006614615,0.972791,0.0001441132,0.02419889],"study_design_scores_gemma":[0.003321827,0.00101382,0.004368764,0.00008710424,0.0003891496,0.0007657743,0.00009284598,0.1423023,0.01770659,0.04850585,0.7786024,0.002843634],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001977925,0.0002735692,0.9933146,0.0008153757,0.00004390219,0.0009472352,0.00001037717,0.0004510389,0.002165923],"genre_scores_gemma":[0.2907889,0.00001337521,0.7063423,0.0008223018,0.0005314156,0.001115249,0.000111479,0.00004047812,0.0002345492],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9242851,"threshold_uncertainty_score":0.8190828,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403584193","doi":"10.1002/nla.2593","title":"Multigrid Reduction‐In‐Time Convergence for Advection Problems: A Fourier Analysis Perspective","year":2024,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Mathematics; Reduction (mathematics); Advection; Convergence (economics); Perspective (graphical); Fourier transform; Fourier analysis; Applied mathematics; Mathematical optimization; Partial differential equation; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01327935357970048,"gpt":0.3005640920308566,"spread":0.2872847384511561,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001520784,0.0001961641,0.0002913954,0.0002830139,0.00007940425,0.00003996949,0.0001600445,0.00007369404,0.0000647022],"category_scores_gemma":[0.00007488253,0.0001769381,0.0001303316,0.002798194,0.00007544563,0.0001562288,0.00001789816,0.000236722,0.0001021332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002393223,"about_ca_system_score_gemma":0.00003547099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009965635,"about_ca_topic_score_gemma":0.000001932332,"domain_scores_codex":[0.998742,0.00002704173,0.0003393282,0.0004195801,0.0002313398,0.0002406705],"domain_scores_gemma":[0.998937,0.0004976166,0.00004220685,0.0002539623,0.0001674447,0.000101773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000219757,0.0001309043,0.0001060549,0.0001860066,0.0005086726,0.000001251999,0.000428348,0.9622602,0.0004430081,0.02814838,0.0001110539,0.007654178],"study_design_scores_gemma":[0.0001396324,0.00005177629,0.0001776639,0.00003052324,0.0002228813,0.00001101407,0.00008299205,0.948155,0.0002841057,0.04518395,0.005427528,0.0002328938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008075841,0.0003687071,0.99634,0.0002737257,0.00008111288,0.00104385,0.00004565858,0.0006424809,0.0003968815],"genre_scores_gemma":[0.1707853,0.00002776904,0.8257255,0.00001969917,0.0002465509,0.00285959,0.00004867095,0.00006908418,0.0002178491],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1706145,"threshold_uncertainty_score":0.7215328,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067594519","doi":"10.1002/nla.428","title":"Asymptotic properties of the <i>QR</i> factorization of banded Hessenberg–Toeplitz matrices","year":2005,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Toeplitz matrix; Mathematics; QR decomposition; Factorization; Diagonal; Matrix decomposition; Matrix (chemical analysis); Combinatorics; Applied mathematics; Algebra over a field; Pure mathematics; Algorithm; Eigenvalues and eigenvectors; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.008905594285361623,"gpt":0.2126713604533317,"spread":0.20376576616797,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001198046,0.0001232089,0.0001885583,0.00004680302,0.0001247014,0.0000241514,0.0007844951,0.00004795494,0.0000179099],"category_scores_gemma":[0.00002110416,0.00007249413,0.00006723402,0.0009535705,0.0001327903,0.0002183935,0.0001147433,0.0001078699,0.00002283428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001760917,"about_ca_system_score_gemma":0.00008516853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001337255,"about_ca_topic_score_gemma":0.000001538008,"domain_scores_codex":[0.9989065,0.00006038968,0.0003252348,0.0002469007,0.0003035855,0.0001573891],"domain_scores_gemma":[0.998812,0.00007238123,0.0002448712,0.0006491527,0.0001607476,0.0000608285],"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":[0.00006196437,0.001128824,0.00298022,0.0002905655,0.0001265173,3.665615e-7,0.001324789,0.007301954,0.02246638,0.9019521,0.0001748075,0.06219146],"study_design_scores_gemma":[0.001662341,0.0004298968,0.006127289,0.0002401866,0.0001780333,0.00004186799,0.0001524961,0.1843442,0.7130809,0.02338942,0.06934007,0.001013357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01022198,0.0002160737,0.987137,0.001137601,0.00003337149,0.0004852232,0.000008571285,0.0000853865,0.000674776],"genre_scores_gemma":[0.957874,0.0000121282,0.04164734,0.0001050167,0.00009497768,0.0000905513,0.000002901059,0.00001024042,0.0001628253],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.947652,"threshold_uncertainty_score":0.2956225,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385694302","doi":"10.1002/nla.2529","title":"Impact of correlated observation errors on the conditioning of variational data assimilation problems","year":2023,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"European Commission; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Data assimilation; Mathematics; Covariance; Weighting; Applied mathematics; Covariance matrix; Condition number; Rate of convergence; Non-linear least squares; Matrix (chemical analysis); Convergence (economics); Diagonal; Conjugate gradient method; Algorithm; Mathematical optimization; Eigenvalues and eigenvectors; Statistics; Computer science; Estimation theory; Key (lock)","retraction":null,"screen_n_in":null,"score":{"opus":0.07422935551257316,"gpt":0.2880792033795224,"spread":0.2138498478669493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003204654,0.00009974738,0.0001548468,0.0000796129,0.000196825,0.00001271271,0.0003038975,0.00005783925,0.001265424],"category_scores_gemma":[0.0001627246,0.00005740991,0.00004446982,0.001350878,0.0001082445,0.0001453085,0.00001768594,0.0001377032,0.0001357813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006063056,"about_ca_system_score_gemma":0.00007801412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001876344,"about_ca_topic_score_gemma":0.00001737517,"domain_scores_codex":[0.9988762,0.00008253437,0.0003416762,0.0002350189,0.0003187555,0.0001458375],"domain_scores_gemma":[0.9980804,0.001022323,0.0002642222,0.0004341022,0.0001366058,0.00006236709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003839927,0.00006225963,0.2631664,0.000006872926,0.00005781621,1.244709e-7,0.00006802156,0.724949,0.00006360073,0.009525431,0.0002683841,0.001793745],"study_design_scores_gemma":[0.0001009478,0.0001324504,0.5546185,0.000005063294,0.00001555257,3.243821e-7,0.00001282075,0.4415484,0.000004065154,0.003370489,0.0001476884,0.00004370265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8606648,0.00002011202,0.1322317,0.00128771,0.00004209121,0.001181125,0.001612743,0.0001335826,0.002826159],"genre_scores_gemma":[0.9904286,0.000004098159,0.002873463,0.00006423844,0.00004207791,0.00002331954,0.006520736,0.000004503996,0.00003896153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2914521,"threshold_uncertainty_score":0.9996476,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3183856668","doi":"10.1002/nla.2399","title":"ODE‐based double‐preconditioning for solving linear systems Aαx=b and f(A)x=b","year":2021,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Carleton University; Statistics Canada","funders":"","keywords":"Ode; Mathematics; Linear system; Computation; Applied mathematics; Ordinary differential equation; Extension (predicate logic); Matrix (chemical analysis); Linear differential equation; System of linear equations; Coefficient matrix; Algebraic number; Algebra over a field; Algorithm; Differential equation; Pure mathematics; Mathematical analysis; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01619017058013841,"gpt":0.2607405617680234,"spread":0.244550391187885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002096429,0.0001717693,0.0002371668,0.0000611527,0.0004365779,0.0002099624,0.0003416225,0.00007576134,0.00002366366],"category_scores_gemma":[0.00002614331,0.0001530534,0.00006290384,0.0006313941,0.00006791412,0.0002518118,0.00009145433,0.000162232,0.0000397948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002409947,"about_ca_system_score_gemma":0.0001551873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009057616,"about_ca_topic_score_gemma":0.000001245455,"domain_scores_codex":[0.9986359,0.00003662499,0.0002778999,0.0005661092,0.0001853094,0.0002981639],"domain_scores_gemma":[0.998534,0.0003542276,0.0001205767,0.0005595451,0.0002419161,0.0001897113],"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":[0.00004484386,0.0002681721,0.0002084012,0.0002011275,0.00007389757,0.000008030979,0.0001484402,0.01086841,0.0006381813,0.9728884,0.0002861088,0.01436603],"study_design_scores_gemma":[0.001341789,0.000117096,0.0001161565,0.00005343169,0.00004133189,0.00007556566,0.00006619158,0.9377169,0.005001758,0.005066174,0.05000401,0.0003995766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001068293,0.0003344435,0.9961058,0.0009586565,0.0000787434,0.0006159748,0.00003212722,0.0002442116,0.000561728],"genre_scores_gemma":[0.3434404,0.000011988,0.6530371,0.0006180779,0.0004834221,0.001630245,0.0001415936,0.00003855527,0.0005986315],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9678222,"threshold_uncertainty_score":0.6241338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389941500","doi":"10.1002/nla.2543","title":"Generalizing reduction‐based algebraic multigrid","year":2023,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Diagonally dominant matrix; Multigrid method; Applied mathematics; Robustness (evolution); Discretization; Condition number; Mathematical optimization; Bounded function; Algorithm; Mathematical analysis; Pure mathematics; Partial differential equation","retraction":null,"screen_n_in":null,"score":{"opus":0.01617655189294508,"gpt":0.2601246523332715,"spread":0.2439481004403264,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002221197,0.0001823234,0.0001707879,0.0001766846,0.0003708526,0.00009165276,0.0007546446,0.00006361598,0.00004863426],"category_scores_gemma":[0.00002094545,0.0001541555,0.00007829357,0.002505217,0.00008805054,0.0001742665,0.0001241262,0.0001840609,0.001163706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002432085,"about_ca_system_score_gemma":0.00009465099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001111231,"about_ca_topic_score_gemma":4.47677e-7,"domain_scores_codex":[0.998438,0.00006819367,0.0002432451,0.0005668902,0.0003109672,0.0003727235],"domain_scores_gemma":[0.9986477,0.00009842219,0.00009378208,0.000854372,0.00009877303,0.0002068742],"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":[0.00004183141,0.000501167,0.0003323967,0.00006935837,0.0001005215,0.00002456943,0.000357142,0.03449962,0.006619319,0.8019335,0.007828075,0.1476925],"study_design_scores_gemma":[0.0007948768,0.0001633627,0.001040699,0.00002094014,0.0000262109,0.00005646858,0.00004032145,0.8211432,0.01034919,0.01834681,0.1473573,0.0006605668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00258726,0.00003692284,0.9926158,0.002561841,0.0001056216,0.000433019,0.000009425376,0.00114557,0.000504523],"genre_scores_gemma":[0.2595185,0.00001703384,0.7356361,0.0009261178,0.0008568615,0.00134102,0.0001402063,0.00005828647,0.001505959],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7866436,"threshold_uncertainty_score":0.999614,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4366774998","doi":"10.1002/nla.2500","title":"A closed‐form multigrid smoothing factor for an additive Vanka‐type smoother applied to the Poisson equation","year":2023,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Numerical methods in engineering","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Poisson's equation; Smoothing; Finite element method; Mathematical analysis; Multigrid method; Applied mathematics; Discretization; Discrete Poisson equation; Partial differential equation; Mixed finite element method; Mass matrix; Laplace's equation","retraction":null,"screen_n_in":null,"score":{"opus":0.03566184032007813,"gpt":0.2983817119453563,"spread":0.2627198716252782,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002285334,0.0003132108,0.0002949715,0.0001504549,0.0002362013,0.00006185732,0.0004246183,0.0001238522,0.00004950235],"category_scores_gemma":[0.0001445504,0.0002381211,0.00007114072,0.001708383,0.0000431191,0.0001333643,0.00004858831,0.0003287639,0.0003913331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001171466,"about_ca_system_score_gemma":0.00002694798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001370407,"about_ca_topic_score_gemma":0.000007173167,"domain_scores_codex":[0.9983354,0.00002789662,0.000340587,0.000447055,0.0003062043,0.0005428477],"domain_scores_gemma":[0.9983243,0.0006227921,0.00006007436,0.0006097758,0.0001202056,0.0002628282],"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":[0.0001383485,0.0001364237,0.00005580768,0.0001125292,0.0002063231,0.000001057454,0.003409732,0.4724203,0.0164347,0.01107905,0.001785348,0.4942203],"study_design_scores_gemma":[0.0005265484,0.0002575342,0.002245731,0.00002437897,0.00005855197,0.000002150718,0.0003312006,0.715124,0.005838426,0.002013496,0.2728923,0.0006857419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006537445,0.00002470699,0.9881756,0.0004134899,0.0001763573,0.002256298,0.0001992582,0.001618301,0.0005985495],"genre_scores_gemma":[0.6479748,0.00001580004,0.3455301,0.0003698639,0.0007764697,0.0047889,0.000223512,0.0002285595,0.00009198485],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6426455,"threshold_uncertainty_score":0.9710295,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2605276264","doi":"10.1002/nla.2095","title":"A stabilized multigrid solver for hyperelastic image registration","year":2017,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Multigrid method; Discretization; Mathematics; Hyperelastic material; Hessian matrix; Solver; Applied mathematics; Mathematical optimization; Regularization (linguistics); Partial differential equation; Finite element method; Computer science; Mathematical analysis; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02607809847944596,"gpt":0.3188376433450104,"spread":0.2927595448655644,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001124031,0.0002029523,0.0002621024,0.00003653437,0.0004010044,0.00008587804,0.0003511234,0.00007217741,0.00002870027],"category_scores_gemma":[0.0004543037,0.0001762116,0.00007441636,0.0001176768,0.0001759891,0.0002194384,0.00003368462,0.000177997,0.00007305981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005649236,"about_ca_system_score_gemma":0.00003008782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002126833,"about_ca_topic_score_gemma":0.00000121198,"domain_scores_codex":[0.9989142,0.00001488111,0.000319606,0.0002919232,0.0002039232,0.0002554448],"domain_scores_gemma":[0.9981182,0.0007151106,0.0001552928,0.0006948163,0.0001789425,0.0001377035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006172622,0.001569394,0.0009781534,0.002002475,0.0006870834,0.00001153131,0.0006345133,0.3487495,0.02797963,0.313861,0.003617127,0.2992923],"study_design_scores_gemma":[0.00106567,0.0001065762,0.0007828866,0.00003267607,0.00007835233,0.00001218917,0.00003186977,0.9111336,0.001852824,0.05579509,0.02864572,0.0004625286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001059916,0.00003315611,0.9954991,0.0002857624,0.00007202355,0.001045052,0.00005256864,0.0003764655,0.001575947],"genre_scores_gemma":[0.1540336,0.000007248706,0.8440808,0.00004228325,0.0002105558,0.001455145,0.00003474789,0.00006507293,0.00007049792],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5623841,"threshold_uncertainty_score":0.71857,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2128985516","doi":"10.1002/nla.1826","title":"Finding off‐diagonal entries of the inverse of a large symmetric sparse matrix","year":2012,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Diagonal; Inverse; Mathematics; Diagonal matrix; Node (physics); Matrix (chemical analysis); Combinatorics; Vertex (graph theory); Algorithm; Block matrix; Band matrix; Square matrix; Symmetric matrix; Eigenvalues and eigenvectors; Geometry; Graph","retraction":null,"screen_n_in":null,"score":{"opus":0.01242476064321722,"gpt":0.2608739387652651,"spread":0.2484491781220479,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003327007,0.0001231455,0.0002061613,0.000111802,0.0001422997,0.00001442995,0.0007558293,0.00005327371,0.00005884272],"category_scores_gemma":[0.0000673292,0.0000810329,0.00009778223,0.001957132,0.000131748,0.0002215602,0.000245246,0.0001575465,0.00005995221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000181699,"about_ca_system_score_gemma":0.00007814502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006948394,"about_ca_topic_score_gemma":8.821312e-7,"domain_scores_codex":[0.9988113,0.00007881787,0.0002970335,0.0001936878,0.0003190793,0.0003000982],"domain_scores_gemma":[0.9986345,0.0002652834,0.0002535619,0.0006247237,0.00009602439,0.0001259242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001344817,0.0004877554,0.01023492,0.00004222981,0.00003954156,3.148591e-7,0.0004013874,0.0001137623,0.000238578,0.9822902,0.000264877,0.005872962],"study_design_scores_gemma":[0.00493291,0.0007302195,0.0680006,0.0002384639,0.0005032626,0.0001993313,0.0008157172,0.2749512,0.1016435,0.04801806,0.4978428,0.002123963],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03665892,0.0003538045,0.9608626,0.0004867915,0.00009410202,0.000505873,0.0000527679,0.00006978442,0.0009153955],"genre_scores_gemma":[0.9201736,0.00001350066,0.07926497,0.0001281649,0.0001185468,0.00008645309,0.000005487735,0.00001041329,0.0001988827],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9342722,"threshold_uncertainty_score":0.3304426,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2945974182","doi":"10.1002/nla.2271","title":"Convergence analysis for parallel‐in‐time solution of hyperbolic systems","year":2019,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland; Verafin (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Partial differential equation; Applied mathematics; Mathematics; Fourier analysis; Convergence (economics); Spacetime; Algebraic number; Fourier transform; Dimension (graph theory); Computer science; Mathematical optimization; Mathematical analysis; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.0241027217736144,"gpt":0.2951315000422264,"spread":0.271028778268612,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002165954,0.0003265781,0.0009782229,0.0002871148,0.00003505989,0.00002077009,0.0004969154,0.0002439836,0.00001969716],"category_scores_gemma":[0.00007289708,0.0003109093,0.0002219828,0.001190963,0.0000835465,0.00004904584,0.0001205249,0.0003911247,0.00005778447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001319018,"about_ca_system_score_gemma":0.00006487951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001430342,"about_ca_topic_score_gemma":6.628857e-7,"domain_scores_codex":[0.9980157,0.00005408372,0.000790048,0.0004784968,0.0003640216,0.0002976635],"domain_scores_gemma":[0.9977444,0.0009165651,0.0003033396,0.0007043339,0.0002263565,0.0001049446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001837802,0.00009121731,0.0008353313,0.0006618091,0.0003722087,1.928985e-7,0.00003340611,0.9935317,0.00007690622,0.003676598,0.00002715634,0.0006751185],"study_design_scores_gemma":[0.0002246269,0.00004009527,0.0008286969,0.00007409791,0.0003469518,0.000001512981,0.0000101056,0.9885278,0.00007453246,0.00851259,0.00102324,0.000335793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002006086,0.0004837387,0.9945943,0.0000422299,0.0001079746,0.002150417,0.0002162371,0.0002112648,0.0001877817],"genre_scores_gemma":[0.351238,0.0000471377,0.6458967,0.00001362124,0.0001010298,0.002326844,0.0002559628,0.00006850112,0.00005212984],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3492319,"threshold_uncertainty_score":0.9999343,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4253510993","doi":"10.1002/nla.258.abs","title":"On the growth factor in Gaussian elimination for generalized Higham matrices","year":2002,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Gaussian elimination; Positive-definite matrix; Hermitian matrix; Mathematics; Gaussian; Matrix (chemical analysis); Class (philosophy); Factor (programming language); Combinatorics; Pure mathematics; Computer science; Physics; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.01661374818348609,"gpt":0.2450198333137332,"spread":0.2284060851302471,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001304436,0.0001402384,0.0001388165,0.00009320819,0.0002081729,0.00008275318,0.0006317405,0.000051186,0.0001080955],"category_scores_gemma":[0.00004340618,0.00008679354,0.00005288446,0.0008296615,0.00004359499,0.0001588,0.00004146391,0.0001382628,0.0001454554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003017404,"about_ca_system_score_gemma":0.00001345031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008931739,"about_ca_topic_score_gemma":0.000001535676,"domain_scores_codex":[0.9989392,0.00006335395,0.0002091618,0.0003482011,0.0002063398,0.0002337486],"domain_scores_gemma":[0.9988487,0.0004702009,0.00009908132,0.0004350247,0.0000684281,0.00007855616],"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":[0.000009372258,0.0001612962,0.0000296172,0.000009124406,0.000007005121,5.728335e-7,0.0001235981,0.00009221931,0.00003405858,0.9865963,0.0004177438,0.01251913],"study_design_scores_gemma":[0.001472485,0.0004775569,0.002022283,0.0000276199,0.00002684389,0.00001248765,0.00003926734,0.8054506,0.002572912,0.149811,0.03747532,0.0006117366],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003305396,0.0000593501,0.9845487,0.009927425,0.00003338033,0.0009015914,0.00001836191,0.0001367137,0.001069051],"genre_scores_gemma":[0.8873215,0.00002574186,0.1093412,0.00109234,0.000171511,0.001608847,0.00001393901,0.00001985745,0.0004050274],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8840161,"threshold_uncertainty_score":0.3539338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2154024134","doi":"10.1002/nla.337","title":"Irreversible Markov processes for phylogenetic models","year":2003,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Markov chain; Markov process; Time reversibility; Markov model; Mathematics; Diversification (marketing strategy); Process (computing); Computer science; Algorithm; Statistical physics; Theoretical computer science; Applied mathematics; Mathematical economics; Markov property; Statistics; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.02116604428217539,"gpt":0.2362803065339344,"spread":0.2151142622517591,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007798847,0.0001241611,0.0001544121,0.00003858984,0.0003199636,0.00001450385,0.0001329147,0.00005420811,0.0002372137],"category_scores_gemma":[0.00004400098,0.00009415966,0.00003503701,0.0004370553,0.0001224988,0.00007468702,0.000003143625,0.00007474054,0.000123059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003061215,"about_ca_system_score_gemma":0.0001032378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003909438,"about_ca_topic_score_gemma":0.0008425224,"domain_scores_codex":[0.9991808,0.00002892256,0.0001450864,0.0002837478,0.0001017249,0.0002597178],"domain_scores_gemma":[0.9992906,0.0002314535,0.00005781689,0.0001726693,0.0001303684,0.0001170572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001891381,0.0002806408,0.9044575,0.000258321,0.000213642,0.000001572335,0.0002728955,0.02237321,0.00001508573,0.0400696,0.005456716,0.02641167],"study_design_scores_gemma":[0.002088381,0.0008289705,0.1939672,0.00002844127,0.000259805,0.00007327571,0.0005637966,0.05382314,0.0002188424,0.05628164,0.6906929,0.001173637],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004505946,0.004093464,0.9274021,0.001208455,0.00006533248,0.001401326,0.0002091685,0.0001623339,0.06095187],"genre_scores_gemma":[0.8947977,0.0001102044,0.1034809,0.0005140892,0.00007332672,0.0001964925,0.000104073,0.00000648942,0.0007166813],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8902918,"threshold_uncertainty_score":0.383972,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3137409987","doi":"10.1002/nla.2426","title":"Low‐order preconditioning of the Stokes equations","year":2021,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Nuclear Security Administration; Office of Science; Advanced Scientific Computing Research; Sandia National Laboratories; U.S. Department of Energy","keywords":"Multigrid method; Discretization; Preconditioner; Order (exchange); Mathematics; Stokes flow; Mathematical analysis; Geometry; Partial differential equation; Linear system; Flow (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.01827425167728905,"gpt":0.2851458680345385,"spread":0.2668716163572494,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001036692,0.0003055806,0.0004446345,0.00007051309,0.0001500026,0.00004260005,0.0005273615,0.0001833462,0.0001129784],"category_scores_gemma":[0.0002701079,0.0002408215,0.0001537645,0.000924787,0.0001834417,0.00007490058,0.0002856235,0.0008154616,0.00001901379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009392322,"about_ca_system_score_gemma":0.0001926572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003206258,"about_ca_topic_score_gemma":0.000001840417,"domain_scores_codex":[0.9983063,0.00008221604,0.0005950134,0.0003694411,0.0004168676,0.0002301707],"domain_scores_gemma":[0.9973488,0.0009936804,0.0002702742,0.0008779111,0.0004115508,0.00009779782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000019925,0.000119515,0.00003917027,0.0003664812,0.0001192698,2.569141e-7,0.0001505177,0.9837541,0.0001394971,0.008339353,0.00004064232,0.00692923],"study_design_scores_gemma":[0.0002924215,0.00003685779,0.00106849,0.0005572346,0.0002511047,0.00001366186,0.0002001965,0.9219814,0.007207948,0.06601663,0.001610795,0.0007632544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00242026,0.0002520455,0.9945396,0.0002248874,0.0001828777,0.0008951841,0.0001125146,0.0002781987,0.001094426],"genre_scores_gemma":[0.2927097,0.00002105574,0.7055672,0.00007674762,0.0001592907,0.001183724,0.0001521008,0.00008345655,0.00004674133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2902894,"threshold_uncertainty_score":0.9820417,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405384795","doi":"10.1002/nla.2608","title":"Quaternion Tensor Completion via <scp>QR</scp> Decomposition and Nuclear Norm Minimization","year":2024,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Fundo para o Desenvolvimento das Ciências e da Tecnologia; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Quaternion; Singular value decomposition; Robustness (evolution); Mathematics; Tensor (intrinsic definition); Matrix completion; Matrix norm; Mathematical optimization; Matrix decomposition; Minification; Singular value; Generalization; Algorithm; Computer science; Artificial intelligence; Mathematical analysis; Pure mathematics; Geometry; Eigenvalues and eigenvectors","retraction":null,"screen_n_in":null,"score":{"opus":0.01797523011889221,"gpt":0.2937145160819113,"spread":0.2757392859630191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001200082,0.0002668258,0.0002787308,0.000167518,0.0003884914,0.0001812051,0.0001709341,0.0001356911,0.00009740958],"category_scores_gemma":[0.00003099943,0.0002326055,0.00008183876,0.0006863258,0.0001338157,0.0002168673,0.00005117305,0.000267705,0.0005854747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007571246,"about_ca_system_score_gemma":0.00002742751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001747393,"about_ca_topic_score_gemma":0.000004383665,"domain_scores_codex":[0.9983234,0.00006123161,0.0004425823,0.0005778738,0.0003105533,0.0002842998],"domain_scores_gemma":[0.9985835,0.0004812967,0.0001326385,0.0004095367,0.0001709985,0.0002220261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000415101,0.001080677,0.0006663635,0.0004388199,0.0002158264,0.000009483281,0.001204314,0.0002224238,0.01131077,0.9484992,0.0135497,0.02276089],"study_design_scores_gemma":[0.001299041,0.0004567694,0.007275081,0.0002374308,0.0005483733,0.0005237065,0.0004857744,0.3668261,0.001556746,0.1132284,0.5069036,0.0006589673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06792718,0.000120038,0.9253675,0.00199936,0.00004735546,0.001213615,0.00009180335,0.00104913,0.002184007],"genre_scores_gemma":[0.8415431,0.00005313109,0.1558496,0.0004643894,0.0003166895,0.000753265,0.0005036327,0.0001186103,0.0003976081],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8352708,"threshold_uncertainty_score":0.9485376,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970518087","doi":"10.1002/nla.2306","title":"A local Fourier analysis of additive Vanka relaxation for the Stokes equations","year":2020,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Discretization; Relaxation (psychology); Convergence (economics); Grid; Applied mathematics; Finite element method; Mathematical optimization; Computer science; Fourier transform; Fourier analysis; Partial differential equation; Algorithm; Mathematics; Mathematical analysis; Geometry; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.03410598634867729,"gpt":0.3163663646694529,"spread":0.2822603783207757,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001785555,0.0003316938,0.0006788041,0.000187953,0.0001542485,0.00002738195,0.0004758216,0.0001837249,0.0000467514],"category_scores_gemma":[0.0004896895,0.0002533907,0.0003339525,0.001825528,0.0002274383,0.00005730489,0.0001399863,0.0005859173,0.00001621467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001184008,"about_ca_system_score_gemma":0.0001001652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000574772,"about_ca_topic_score_gemma":0.000003014955,"domain_scores_codex":[0.9981247,0.00005613532,0.0007088553,0.0004463367,0.0004346186,0.0002293585],"domain_scores_gemma":[0.9931839,0.005189206,0.0004003294,0.0006698598,0.0004255737,0.0001311293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002098742,0.00006043633,0.000005894782,0.0001239224,0.00164246,1.727735e-7,0.000213092,0.9164301,0.00001280452,0.04248243,0.0001372047,0.03887055],"study_design_scores_gemma":[0.0001386807,0.00004929495,0.0001841205,0.00002576724,0.002224632,5.023807e-7,0.000109983,0.9267685,0.0001412476,0.06458561,0.005513983,0.0002576606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000435346,0.0002389354,0.9953238,0.0009070934,0.00007036934,0.001833859,0.001076075,0.000289997,0.000216331],"genre_scores_gemma":[0.2085285,0.00004103395,0.7860054,0.0001159382,0.0001784863,0.00424329,0.0007904454,0.00008121486,0.00001560239],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2093184,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105813930","doi":"10.1002/nla.730","title":"A note on simultaneous preconditioning and symmetrization of non-symmetric linear systems","year":2010,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts","keywords":"Symmetrization; Mathematics; Duality (order theory); Applied mathematics; Partial differential equation; Linear system; Scheme (mathematics); Iterative method; Mathematical optimization; Mathematical analysis; Pure mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.008644112826970859,"gpt":0.2754375070949733,"spread":0.2667933942680024,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001201765,0.0001994928,0.0003062494,0.0001722817,0.00009743249,0.00002083982,0.0001523216,0.0001143734,0.00001162438],"category_scores_gemma":[0.0004442409,0.0001774801,0.00003573254,0.001284744,0.00009965731,0.00008241067,0.00002464496,0.0003939704,0.00003644723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002932138,"about_ca_system_score_gemma":0.00001770311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003402012,"about_ca_topic_score_gemma":4.140443e-7,"domain_scores_codex":[0.9988359,0.00002283863,0.0004050176,0.0002656973,0.0002754498,0.0001950514],"domain_scores_gemma":[0.9971131,0.002089693,0.0001416636,0.0003119804,0.000199223,0.0001443452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001846027,0.0001481929,0.0001180942,0.0002419678,0.00004688016,0.0000012326,0.00007302342,0.9102312,0.002243946,0.02521484,0.00001139071,0.06165072],"study_design_scores_gemma":[0.000258889,0.0001437685,0.000292415,0.00003817931,0.00003281875,0.00002052602,0.00001587283,0.9928413,0.002093542,0.002437692,0.001605051,0.0002199491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01580784,0.00004565699,0.9821517,0.00003420548,0.0001027682,0.0006422055,0.00004083368,0.0002250293,0.0009497605],"genre_scores_gemma":[0.5790039,0.000008682203,0.4205964,0.00002142918,0.000117772,0.0001754418,0.00002429455,0.00004079761,0.0000112834],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5631961,"threshold_uncertainty_score":0.723743,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1984710842","doi":"10.1002/nla.240","title":"Lanczos, Householder transformations, and implicit deflation for fast and reliable dominant singular subspace computation","year":2001,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of California, San Diego; California State University San Marcos; McGill University; University of California Berkeley","keywords":"Lanczos resampling; Lanczos algorithm; Linear subspace; Mathematics; Computation; Krylov subspace; Subspace topology; Matrix (chemical analysis); Singular value; Signal subspace; Algorithm; Numerical linear algebra; Applied mathematics; Algebra over a field; Sparse matrix; Singular spectrum analysis; Singular value decomposition; Eigenvalues and eigenvectors; Pure mathematics; Mathematical analysis; Computer science; Numerical analysis; Iterative method; Noise (video); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.009264214916319834,"gpt":0.2428126637843949,"spread":0.2335484488680751,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001752194,0.0001391296,0.0001650991,0.00007182411,0.0003654445,0.000117474,0.0001472439,0.00005872476,0.000002848576],"category_scores_gemma":[0.000008924587,0.0001169489,0.00002695386,0.0004301059,0.00005941339,0.000371449,0.0000304352,0.00009099796,0.000008172351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001678265,"about_ca_system_score_gemma":0.00002942352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001325043,"about_ca_topic_score_gemma":0.000002709168,"domain_scores_codex":[0.9990791,0.00002334288,0.0002166529,0.0003336665,0.0001335624,0.0002136719],"domain_scores_gemma":[0.999326,0.0001370888,0.00009073457,0.0002244648,0.00009763661,0.0001240576],"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":[0.0001295886,0.000323952,0.00229076,0.0001555794,0.0000625971,0.000003218681,0.001345689,0.003923623,0.001040933,0.6521277,0.0003970621,0.3381993],"study_design_scores_gemma":[0.001512217,0.0002503428,0.002984873,0.00002857084,0.00005373423,0.000159933,0.0001109846,0.9023059,0.0009080712,0.03977545,0.05148076,0.000429155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01042607,0.0001811272,0.986819,0.001371072,0.00001692971,0.0008147849,0.00001146971,0.0001377206,0.0002218254],"genre_scores_gemma":[0.5023462,0.00007875192,0.4965393,0.0003246136,0.0000957372,0.0004500388,0.0000523195,0.00002187203,0.00009120355],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8983823,"threshold_uncertainty_score":0.4769036,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4379648388","doi":"10.1002/nla.2514","title":"A Vanka‐based parameter‐robust multigrid relaxation for the Stokes–Darcy Brinkman problems","year":2023,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Mathematics; Multigrid method; Discretization; Mathematical analysis; Applied mathematics; Relaxation (psychology); Stokes flow; Darcy number; Partial differential equation; Geometry; Physics; Flow (mathematics); Mechanics; Reynolds number","retraction":null,"screen_n_in":null,"score":{"opus":0.0439613445610292,"gpt":0.2994658209317939,"spread":0.2555044763707647,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002508638,0.0002437561,0.0002507422,0.0001023846,0.0002879933,0.00006375361,0.0003499268,0.00008517078,0.00001546501],"category_scores_gemma":[0.0003243845,0.0001779341,0.0001004505,0.001377219,0.0001191018,0.0001489032,0.00003559399,0.0002953588,0.0001723538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007299954,"about_ca_system_score_gemma":0.00003498117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003295893,"about_ca_topic_score_gemma":0.000001207125,"domain_scores_codex":[0.9985141,0.00003837173,0.0004075085,0.0003395571,0.0003282384,0.0003722687],"domain_scores_gemma":[0.9952207,0.003857621,0.0001219653,0.0005098268,0.0001617027,0.0001281998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001356717,0.00005726142,0.00005238258,0.0001246307,0.00004862528,4.687664e-7,0.00006648421,0.963038,0.0001122492,0.006559282,0.0003756697,0.02955142],"study_design_scores_gemma":[0.0003923897,0.00007258743,0.0004397094,0.00002461431,0.00005103555,0.000005005586,0.00003358668,0.9500084,0.0002268103,0.01686464,0.03163379,0.0002474024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005138355,0.00008015957,0.9948094,0.001032842,0.00008462038,0.00204341,0.00007138308,0.001209001,0.0001552905],"genre_scores_gemma":[0.0889541,0.00002250826,0.904202,0.0002112823,0.0002310939,0.005974335,0.0001709094,0.0001205944,0.0001131781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09060746,"threshold_uncertainty_score":0.7255943,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2779052738","doi":"10.1002/nla.2206","title":"A multigrid solver to the Helmholtz equation with a point source based on travel time and amplitude","year":2018,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Seventh Framework Programme","keywords":"Helmholtz equation; Discretization; Multigrid method; Solver; Wave equation; Mathematical analysis; Eikonal equation; Mathematics; Amplitude; Applied mathematics; Partial differential equation; Physics; Mathematical optimization; Boundary value problem","retraction":null,"screen_n_in":null,"score":{"opus":0.01385753378964502,"gpt":0.2245611686145886,"spread":0.2107036348249436,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002831622,0.0002978902,0.0002668498,0.0001183602,0.00032673,0.0001309184,0.0003908997,0.0001244242,0.0004049545],"category_scores_gemma":[0.0000322173,0.0001732319,0.00005371534,0.0003226075,0.0002427877,0.00005087926,0.00005045582,0.0004605901,0.0006940999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001465212,"about_ca_system_score_gemma":0.00012425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650241,"about_ca_topic_score_gemma":0.00002783154,"domain_scores_codex":[0.9983005,0.00007813598,0.0002307084,0.0006762086,0.0004214147,0.0002930206],"domain_scores_gemma":[0.9985687,0.0002360211,0.0001523022,0.000690231,0.0001237879,0.0002289421],"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":[0.002937861,0.001146162,0.02870463,0.0003603794,0.0004806077,0.00001525233,0.003665513,0.2792699,0.0001626651,0.0005952385,0.08603374,0.596628],"study_design_scores_gemma":[0.0003031527,0.0005864431,0.008524162,0.0001107915,0.00006947916,0.00000996883,0.0000585303,0.9235801,0.0003434096,0.0003414211,0.06565847,0.0004141422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006427845,0.0000455016,0.9804632,0.00906142,0.00003107623,0.001731314,0.0002425575,0.0002636122,0.00173349],"genre_scores_gemma":[0.8138107,0.0000124271,0.1657722,0.01780007,0.0005092994,0.0003782685,0.001102395,0.00003862591,0.0005759882],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8146909,"threshold_uncertainty_score":0.8921482,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}