{"meta":{"query_hash":"65d2aabcbca5","filters":{"venue":"Numerical Linear Algebra with Applications"},"cohort_total":58,"direct_labels_cover":0,"predictions_cover":58,"exported":58,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/65d2aabcbca5","api":"https://metacan.xera.ac/api/v1/cohort?venue=Numerical+Linear+Algebra+with+Applications"},"results":[{"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.02959064902754927,"score_gpt":0.3115063589447691,"score_spread":0.2819157099172198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1636009176","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004528983,0.0003587512,0.9907041,0.00019185599,0.000064278844,0.00004191505,0.0001103607,0.00031569652,0.0036841233],"genre_scores_gemma":[0.23717389,0.0009540973,0.7521833,0.00017595045,0.00015763586,0.0004803585,0.0004021294,0.00043982227,0.008032754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993363,0.0002524014,0.000026387906,0.000048498146,0.0002796724,0.000056571043],"domain_scores_gemma":[0.9984363,0.00084030215,0.000113652924,0.00021786022,0.00031315885,0.00007878193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090607314,0.00045533915,0.00075358833,0.0007289519,0.00062472327,0.0008108701,0.00094164425,0.0007493626,0.0056310096],"category_scores_gemma":[0.0038370392,0.00034685177,0.0009088529,0.0007933197,0.0005555101,0.00081204466,0.0014598353,0.0015096011,0.0013840061],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006838573,0.000041630497,0.00076349295,0.00027341774,0.00009681033,0.00011657893,0.00021580416,0.5838642,0.0044429693,0.29549065,0.0062660687,0.10836002],"study_design_scores_gemma":[0.000009919888,0.000007157071,0.00006530813,0.000013512538,0.000003979197,0.000012132122,0.000009062066,0.96455693,0.0004125836,0.03198172,0.002921365,0.000006211379],"about_ca_topic_score_codex":0.004073597,"about_ca_topic_score_gemma":0.004204821,"teacher_disagreement_score":0.0056310096,"about_ca_system_score_codex":0.0006700098,"about_ca_system_score_gemma":0.001210728,"threshold_uncertainty_score":0.018837571},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.03789095206775524,"score_gpt":0.364729005794814,"score_spread":0.32683805372705876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1796252776","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030525771,0.00022798375,0.9917374,0.00021207138,0.000068044,0.000027133021,0.00007127599,0.0004782061,0.004125214],"genre_scores_gemma":[0.46646446,0.00096776226,0.51782143,0.00037036592,0.00035647713,0.00049736263,0.00042101488,0.0009920603,0.01210903],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995479,0.00017596713,0.000020517886,0.000042597163,0.00018263498,0.00003039968],"domain_scores_gemma":[0.99883205,0.00063867896,0.00009342458,0.00019660262,0.00020229808,0.00003685383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013700632,0.0006824944,0.0005709485,0.00116745,0.00041742917,0.0011517017,0.0011872516,0.0008510691,0.0054209754],"category_scores_gemma":[0.003858005,0.0003158594,0.00113248,0.0007495711,0.00099904,0.0009962365,0.0017702626,0.001992318,0.0012629932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029863435,0.000027836712,0.00053143915,0.00012365673,0.000040590647,0.00015585605,0.00015757747,0.32549676,0.0041339966,0.61234033,0.0036277038,0.053334445],"study_design_scores_gemma":[0.0000031053648,0.0000048600245,0.000049385057,0.000012996267,0.0000036436825,0.000014185251,0.000007831995,0.92426205,0.00043938207,0.0714388,0.003759139,0.0000046679106],"about_ca_topic_score_codex":0.0017584739,"about_ca_topic_score_gemma":0.0012864219,"teacher_disagreement_score":0.0054209754,"about_ca_system_score_codex":0.0005116816,"about_ca_system_score_gemma":0.0007047605,"threshold_uncertainty_score":0.018135011},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.012650691698895641,"score_gpt":0.25487471741778867,"score_spread":0.242224025718893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1840032205","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022318464,0.0010624613,0.96481264,0.00064354355,0.00012382082,0.00005170833,0.00015539529,0.00021327136,0.010618729],"genre_scores_gemma":[0.45952874,0.0022675938,0.52312523,0.0005322347,0.0004556984,0.0006309741,0.0007714462,0.00057664764,0.012111316],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950788,0.0019862494,0.00024360266,0.000586107,0.0017814544,0.00032374726],"domain_scores_gemma":[0.95607674,0.033265356,0.0022466036,0.0020741108,0.0054079876,0.00092906586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00838121,0.0016912936,0.0012094105,0.0023503697,0.001028229,0.0035547123,0.0016829746,0.0018386102,0.0103401635],"category_scores_gemma":[0.047694445,0.00065682025,0.0007478701,0.0016305215,0.004714347,0.00774918,0.0027251341,0.0046936604,0.0024539183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003731269,0.0000934403,0.001220709,0.00052735576,0.000044060773,0.00023766386,0.00028221938,0.1333966,0.0114688445,0.7967519,0.0053517614,0.050252326],"study_design_scores_gemma":[0.000016305337,0.000076286036,0.000384989,0.00013041291,0.000013145249,0.00010724507,0.000074336305,0.72739154,0.007621608,0.26164064,0.0024768163,0.000066678695],"about_ca_topic_score_codex":0.0012054627,"about_ca_topic_score_gemma":0.0011187221,"teacher_disagreement_score":0.0103401635,"about_ca_system_score_codex":0.0013614583,"about_ca_system_score_gemma":0.001671343,"threshold_uncertainty_score":0.044324577},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.03708464711442809,"score_gpt":0.37598441701929824,"score_spread":0.33889976990487014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1919986261","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00893404,0.00019570775,0.9849979,0.00024014019,0.00008830169,0.000028909735,0.000051474202,0.00009428603,0.00536926],"genre_scores_gemma":[0.30784014,0.00083392044,0.67598706,0.0002654018,0.00027995443,0.00021081776,0.00021908327,0.00039395483,0.013969666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991597,0.00032436676,0.000049465474,0.0001175636,0.00028223454,0.000066627596],"domain_scores_gemma":[0.99809283,0.00083014945,0.00017346507,0.00035927686,0.00040622355,0.00013806674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017575275,0.00058500085,0.0007497525,0.001000554,0.00069196837,0.0014211913,0.00089684996,0.0004885158,0.0038544973],"category_scores_gemma":[0.0048152013,0.00035042776,0.00075617374,0.00076431973,0.002267868,0.0023844116,0.0018310368,0.0015057126,0.0011407047],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026685404,0.000018805167,0.00018332542,0.000048145586,0.000012658915,0.00006169577,0.000114182265,0.046411023,0.0022085216,0.92314404,0.0018540177,0.02591686],"study_design_scores_gemma":[0.000008564423,0.000021696475,0.00007188995,0.000014673123,0.0000045892357,0.0000421493,0.000035127363,0.37791747,0.0017652926,0.61449003,0.0056137387,0.000014824947],"about_ca_topic_score_codex":0.0012915098,"about_ca_topic_score_gemma":0.0013262565,"teacher_disagreement_score":0.0038544973,"about_ca_system_score_codex":0.0006414873,"about_ca_system_score_gemma":0.0010958131,"threshold_uncertainty_score":0.012894511},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.01219782384400975,"score_gpt":0.2882343383597085,"score_spread":0.27603651451569877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976129499","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044096997,0.00029808297,0.98982555,0.00039267744,0.000054323988,0.000043988333,0.000044004362,0.00014464474,0.0047869827],"genre_scores_gemma":[0.27253267,0.00052512763,0.7136657,0.00027926004,0.00012395151,0.00052272505,0.0002636098,0.0004544854,0.011632446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884534,0.00051533146,0.000054589156,0.0001833125,0.00034612903,0.000055303688],"domain_scores_gemma":[0.9981957,0.0011850803,0.00018795226,0.00013019942,0.00023822421,0.000062798536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019292112,0.0009283495,0.0011805951,0.0009977982,0.00054725836,0.0013137927,0.0009995422,0.002033455,0.0053343074],"category_scores_gemma":[0.008281821,0.0005964149,0.0007667409,0.0008587083,0.0021455307,0.001222256,0.0026081286,0.0015883665,0.00090652815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062065425,0.000032153705,0.0002673379,0.00014905089,0.000034838034,0.00007975069,0.000081733764,0.85638136,0.0027427024,0.11079377,0.0020559009,0.02731934],"study_design_scores_gemma":[0.000008782651,0.000009175971,0.00004219904,0.000009309296,0.0000030623944,0.00001532945,0.0000067295914,0.9711638,0.00033980477,0.026732989,0.0016642886,0.0000044544404],"about_ca_topic_score_codex":0.0033435647,"about_ca_topic_score_gemma":0.0022092515,"teacher_disagreement_score":0.0053343074,"about_ca_system_score_codex":0.0012501618,"about_ca_system_score_gemma":0.0014014343,"threshold_uncertainty_score":0.017845094},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.02501987492455005,"score_gpt":0.33267217644731356,"score_spread":0.3076523015227635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983085277","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017590566,0.000028857288,0.9976053,0.000015648759,0.000023731065,0.000014405689,0.000012262429,0.00015536157,0.00038526522],"genre_scores_gemma":[0.052889355,0.00013237746,0.945217,0.000033222343,0.000037716138,0.00007249841,0.00008519564,0.00014298013,0.0013896485],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995659,0.00013223845,0.000028946723,0.000051088275,0.00018443516,0.00003739866],"domain_scores_gemma":[0.9991658,0.00031206466,0.00006255075,0.00015562076,0.00024856886,0.000055453005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007293417,0.00086565147,0.00072267797,0.0008847496,0.0005192989,0.000810094,0.0007721268,0.00050812506,0.007360427],"category_scores_gemma":[0.0028149837,0.00027462246,0.0008451613,0.00066366006,0.0009228161,0.0011616588,0.001130284,0.00096373877,0.002661404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002988657,0.00008033512,0.000798249,0.00040069464,0.000111982336,0.00050719496,0.00047752142,0.25040933,0.05009967,0.15590353,0.007060463,0.53385216],"study_design_scores_gemma":[0.000028409864,0.00006228669,0.00007861087,0.000022739945,0.000013417233,0.00014943267,0.00005154365,0.95780593,0.0077824146,0.029065695,0.0049175113,0.000022073506],"about_ca_topic_score_codex":0.0017835066,"about_ca_topic_score_gemma":0.001907623,"teacher_disagreement_score":0.007360427,"about_ca_system_score_codex":0.00032095241,"about_ca_system_score_gemma":0.0009266179,"threshold_uncertainty_score":0.024623096},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.009264214916319834,"score_gpt":0.24281266378439495,"score_spread":0.2335484488680751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984710842","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012883556,0.00022770198,0.98387825,0.00010885553,0.000052069063,0.00003251151,0.000036465444,0.0014362958,0.0013442319],"genre_scores_gemma":[0.15128455,0.0002454309,0.8447849,0.00004929823,0.000039564897,0.000102485435,0.000151334,0.0002130296,0.0031292755],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99948573,0.0001868343,0.000034090204,0.00003885027,0.00021693896,0.00003748446],"domain_scores_gemma":[0.9989385,0.00044648984,0.00011125273,0.00023059202,0.00022313434,0.00005004888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084923755,0.0006318812,0.0006224921,0.00046963527,0.00043953196,0.0007287428,0.0006677054,0.0005209873,0.0037297728],"category_scores_gemma":[0.004012063,0.0003087602,0.00031905848,0.00083187176,0.0007053716,0.0011662617,0.0009280651,0.0008507602,0.001541096],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047594708,0.000079652295,0.0009653967,0.00023881212,0.00007484076,0.00029163816,0.0003847297,0.38225672,0.032632012,0.11911534,0.011724137,0.4517608],"study_design_scores_gemma":[0.00003290422,0.00003058044,0.00007774585,0.0000060972134,0.0000039340634,0.000028260392,0.00001112844,0.98329103,0.0045402106,0.009233357,0.0027359494,0.000008815284],"about_ca_topic_score_codex":0.003710185,"about_ca_topic_score_gemma":0.004633211,"teacher_disagreement_score":0.0037297728,"about_ca_system_score_codex":0.00037315174,"about_ca_system_score_gemma":0.0010169647,"threshold_uncertainty_score":0.012477279},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.030253191888310074,"score_gpt":0.26643519081247596,"score_spread":0.2361819989241659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992234740","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.104013056,0.0001972269,0.8763393,0.00028236283,0.00009698285,0.000073709416,0.00012455315,0.00081866863,0.018054146],"genre_scores_gemma":[0.6333237,0.00021279798,0.35676852,0.00009199596,0.00007514394,0.0002055337,0.00020904592,0.00018606537,0.008927242],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979705,0.00004151699,0.00000937087,0.000023340815,0.000104963336,0.00002365102],"domain_scores_gemma":[0.99967897,0.00009839831,0.000043169854,0.00006864031,0.00008363749,0.000027254267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003147394,0.00049151684,0.0006537576,0.0002723184,0.00030294884,0.0005767533,0.00067963975,0.00041951452,0.0022758024],"category_scores_gemma":[0.00079525047,0.00027711742,0.0004453082,0.0003342005,0.0004712936,0.00064132776,0.0009705552,0.0004112733,0.0005038307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012038038,0.00007936816,0.00091900205,0.000096409894,0.00005851583,0.00025923748,0.00010553402,0.8751758,0.028885243,0.043909136,0.0021515975,0.04823973],"study_design_scores_gemma":[0.000013740504,0.000012367156,0.00007657234,0.000001747759,0.0000028889608,0.00001962396,0.000005130316,0.9941865,0.0019999323,0.0027696695,0.00090856664,0.0000031870013],"about_ca_topic_score_codex":0.0015292809,"about_ca_topic_score_gemma":0.0012564935,"teacher_disagreement_score":0.0022758024,"about_ca_system_score_codex":0.00026495833,"about_ca_system_score_gemma":0.0005859455,"threshold_uncertainty_score":0.0076133013},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.004614076783061271,"score_gpt":0.25739552059739856,"score_spread":0.2527814438143373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010972644","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13371232,0.00024006459,0.8166924,0.00041910715,0.00028022466,0.00013273605,0.000120241566,0.00051085395,0.047892105],"genre_scores_gemma":[0.72771865,0.00025464254,0.2492599,0.00032147145,0.0002718921,0.00012929903,0.0002191908,0.00031012224,0.021514941],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986406,0.0003109114,0.0000846598,0.00026681938,0.0004787325,0.0002183],"domain_scores_gemma":[0.9987809,0.00019637968,0.00013069685,0.00022464147,0.00045776446,0.00020948553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010704936,0.000837773,0.00055122154,0.0013628892,0.001012032,0.0018326882,0.00073360925,0.0008400777,0.010523121],"category_scores_gemma":[0.0024938695,0.000426241,0.00081643777,0.0008321556,0.0016014032,0.002764714,0.0020846198,0.0017061206,0.0018839362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052424242,0.000060228285,0.00030071783,0.000069405425,0.000011658851,0.00027528207,0.00027190818,0.0064046066,0.017072454,0.9502063,0.0024179379,0.022857133],"study_design_scores_gemma":[0.000018476047,0.00016051342,0.00028229156,0.00002965009,0.00001327997,0.00042204442,0.00030587116,0.09938949,0.009347797,0.8799758,0.010012353,0.000042469324],"about_ca_topic_score_codex":0.00025599325,"about_ca_topic_score_gemma":0.0004638554,"teacher_disagreement_score":0.010523121,"about_ca_system_score_codex":0.00030574686,"about_ca_system_score_gemma":0.0006933444,"threshold_uncertainty_score":0.035203338},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.015150813886271673,"score_gpt":0.2651078357017424,"score_spread":0.24995702181547072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013095747","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0224529,0.00010344739,0.974069,0.00017497658,0.000023581864,0.00004616656,0.000037389033,0.0006438886,0.0024487854],"genre_scores_gemma":[0.24304357,0.00009340774,0.75326014,0.0001104133,0.000051526833,0.00025433485,0.00013005018,0.00022390968,0.0028326737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99911004,0.00036404308,0.000032226675,0.00011002561,0.000265698,0.00011786118],"domain_scores_gemma":[0.9973889,0.0018544229,0.00012776545,0.00026129652,0.0002707992,0.000096786825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017433761,0.00079835556,0.0011922517,0.0015828093,0.0011079478,0.0012322529,0.0013193947,0.0010069966,0.0051942696],"category_scores_gemma":[0.005735911,0.0005543877,0.0008631179,0.0011144414,0.0017477318,0.002269824,0.0014177752,0.0016930246,0.00089903345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000522463,0.00020461594,0.0008262415,0.00017466121,0.00010065442,0.00018203614,0.00025675274,0.5494545,0.0066715847,0.24641144,0.003092748,0.19210225],"study_design_scores_gemma":[0.000026110643,0.000016640712,0.00004518447,0.0000051803436,0.0000055612286,0.000011682215,0.000012669465,0.93678635,0.001605578,0.060950696,0.00052735774,0.000007008857],"about_ca_topic_score_codex":0.0054566194,"about_ca_topic_score_gemma":0.00735388,"teacher_disagreement_score":0.0054566194,"about_ca_system_score_codex":0.0012975779,"about_ca_system_score_gemma":0.0016733356,"threshold_uncertainty_score":0.017376602},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.028432037537596853,"score_gpt":0.302662501843118,"score_spread":0.2742304643055211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018978449","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037003565,0.00017859138,0.99420434,0.00023837574,0.000040407693,0.000027132144,0.000032207772,0.00008050965,0.0014980494],"genre_scores_gemma":[0.4348768,0.0011824992,0.5493016,0.00054668926,0.00028359686,0.0006364951,0.0005515792,0.00046762972,0.012153049],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976331,0.0012635092,0.00008050604,0.00019013965,0.0007446362,0.00008816397],"domain_scores_gemma":[0.9907871,0.0072084274,0.00041771648,0.00029473024,0.0011321817,0.00015977432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004084817,0.0012980229,0.0009490141,0.0009626371,0.0005835693,0.0010890777,0.0009549004,0.0011267713,0.0035783947],"category_scores_gemma":[0.0139030125,0.00051813136,0.0008846375,0.0006473193,0.0016795708,0.0014123854,0.0023254768,0.002051409,0.00065337546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011665508,0.00003705419,0.0006995327,0.0002254744,0.00006835989,0.00017805307,0.00008855146,0.8608255,0.0040767193,0.10315509,0.0023463399,0.028182779],"study_design_scores_gemma":[0.0000041130597,0.000010307689,0.000055655666,0.000010553508,0.0000033637239,0.000011471545,0.000008417249,0.9761524,0.00057581445,0.022668364,0.00049458916,0.000004957031],"about_ca_topic_score_codex":0.0030457217,"about_ca_topic_score_gemma":0.0014805271,"teacher_disagreement_score":0.004084817,"about_ca_system_score_codex":0.001106459,"about_ca_system_score_gemma":0.0010955344,"threshold_uncertainty_score":0.02160281},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.01661374818348609,"score_gpt":0.2450198333137332,"score_spread":0.2284060851302471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056707245","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20453547,0.0018964815,0.7575524,0.0022384063,0.00042718532,0.000106162384,0.0001350805,0.00073143176,0.032377314],"genre_scores_gemma":[0.90886915,0.0012544246,0.075679965,0.0005004446,0.0003072659,0.00015729462,0.00019571657,0.0004493878,0.012586391],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977963,0.00092307414,0.000053844313,0.00014605878,0.0007912375,0.00028943922],"domain_scores_gemma":[0.9787139,0.016023451,0.0010213937,0.0012485922,0.0022703493,0.000722311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040423316,0.0011683049,0.0008322928,0.0013093443,0.0012091785,0.0014478423,0.0009971011,0.0010992509,0.005591102],"category_scores_gemma":[0.029121669,0.00035910393,0.000590584,0.0008319835,0.003661128,0.0031888478,0.002272069,0.0021319857,0.0014002803],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047226108,0.00008507443,0.0026350962,0.00021551263,0.000038582762,0.00045551072,0.0004094392,0.08486697,0.00749488,0.8528371,0.008316772,0.042172916],"study_design_scores_gemma":[0.000038315648,0.00009801802,0.0005205221,0.000076309065,0.00001585285,0.00031346505,0.000086893735,0.577813,0.0071844724,0.4102465,0.0035461674,0.000060388935],"about_ca_topic_score_codex":0.0023781813,"about_ca_topic_score_gemma":0.0022777533,"teacher_disagreement_score":0.005591102,"about_ca_system_score_codex":0.0011549598,"about_ca_system_score_gemma":0.00095894944,"threshold_uncertainty_score":0.0213781},"labels":[],"label_agreement":null},{"id":"W2063957170","doi":"10.1002/nla.521","title":"Mathematical Modelling and Mathematical Methods in Energy","year":2006,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Fundação Araucária","keywords":"Library science; Bachelor; Mathematics; Operations research; Geography; Computer science; Archaeology","score_opus":0.013189107157339524,"score_gpt":0.2776829384344822,"score_spread":0.2644938312771427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063957170","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044902936,0.101568334,0.78611124,0.014900421,0.0068219425,0.00009161753,0.00062059925,0.0006891271,0.08470647],"genre_scores_gemma":[0.31163123,0.15111884,0.37273657,0.00631284,0.01628585,0.00092871924,0.0018402266,0.0014324258,0.13771321],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99767977,0.0009481757,0.00015434867,0.0003452882,0.0007416215,0.00013073903],"domain_scores_gemma":[0.9979911,0.001012492,0.00021417078,0.0003187698,0.00038153352,0.00008194801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023427578,0.0015794429,0.0018672753,0.0026087451,0.0008696483,0.0040000123,0.0013315222,0.002180955,0.0074155787],"category_scores_gemma":[0.0035388798,0.0005478366,0.0027391673,0.0021706054,0.003970267,0.0035186687,0.0023683344,0.005723285,0.004387181],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001833853,0.000024602463,0.00024572905,0.000513454,0.000072738025,0.00012970887,0.00027077645,0.016028944,0.0013372463,0.92513937,0.02039902,0.03582004],"study_design_scores_gemma":[0.000009319901,0.00003788788,0.00034575284,0.00019953908,0.000024169512,0.00023349201,0.00008075381,0.032328956,0.000612756,0.80476826,0.16132806,0.00003108154],"about_ca_topic_score_codex":0.0016620038,"about_ca_topic_score_gemma":0.00084006763,"teacher_disagreement_score":0.0074155787,"about_ca_system_score_codex":0.0020392286,"about_ca_system_score_gemma":0.0015902618,"threshold_uncertainty_score":0.024807632},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.008905594285361623,"score_gpt":0.21267136045333165,"score_spread":0.20376576616797004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067594519","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07559112,0.00032959488,0.91647804,0.00025354404,0.00004776963,0.000034647845,0.000085233725,0.00045565303,0.00672438],"genre_scores_gemma":[0.84260947,0.00050245377,0.1509002,0.00012573054,0.00007406481,0.00009370575,0.00033607136,0.00023909804,0.0051192935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99931467,0.00025761564,0.000028838227,0.000082702245,0.00023562666,0.00008050819],"domain_scores_gemma":[0.99496704,0.0025837277,0.00063916954,0.0006536933,0.00097471004,0.00018161048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019900184,0.00053760293,0.00040940466,0.0005299513,0.00029939733,0.00086850795,0.0004624193,0.0004318408,0.0048472034],"category_scores_gemma":[0.013733727,0.0003094548,0.00030460692,0.00037710907,0.0014618997,0.0014487596,0.0007673286,0.0008304885,0.0011687736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003679301,0.00007495579,0.002310853,0.00028299406,0.000054501816,0.00034678978,0.00043802444,0.5236498,0.031327527,0.38274908,0.004103674,0.054293867],"study_design_scores_gemma":[0.0000113299475,0.000050027556,0.0005035609,0.00002957704,0.0000050913045,0.00008531094,0.000057982197,0.9534612,0.003977871,0.040543064,0.0012581769,0.00001683145],"about_ca_topic_score_codex":0.0021096687,"about_ca_topic_score_gemma":0.0012302159,"teacher_disagreement_score":0.0048472034,"about_ca_system_score_codex":0.00052776,"about_ca_system_score_gemma":0.00063191913,"threshold_uncertainty_score":0.016215503},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.006816845117285113,"score_gpt":0.24769655799835003,"score_spread":0.2408797128810649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099359799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022453936,0.000072902505,0.973783,0.00015739285,0.000070531074,0.00003562515,0.000042328797,0.00020283843,0.0031814324],"genre_scores_gemma":[0.3733261,0.0002189249,0.6194242,0.00013315876,0.00009899294,0.0002534786,0.00014547953,0.00016141061,0.0062382556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997019,0.000108264576,0.000014231645,0.000021510285,0.00013000747,0.000024036584],"domain_scores_gemma":[0.9996043,0.00015600266,0.0000540493,0.00006532746,0.00008937879,0.000030912943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055885105,0.00043127412,0.0003720976,0.00024924893,0.00027935684,0.00049210613,0.00043066154,0.0005530901,0.0035319452],"category_scores_gemma":[0.001666185,0.00019902614,0.00036423138,0.00022179185,0.00062869204,0.00054205576,0.0009721613,0.00076189847,0.00064137485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002693734,0.00010958147,0.0008928794,0.00022169384,0.00006743809,0.0003026512,0.0002924951,0.5286477,0.059185434,0.28131953,0.0045470083,0.12414424],"study_design_scores_gemma":[0.000020569545,0.0000317474,0.00008391626,0.0000060596108,0.000003942361,0.000020935935,0.000013166606,0.9835398,0.0033964477,0.010491405,0.0023872498,0.000004867507],"about_ca_topic_score_codex":0.001206961,"about_ca_topic_score_gemma":0.0015193577,"teacher_disagreement_score":0.0035319452,"about_ca_system_score_codex":0.0002293608,"about_ca_system_score_gemma":0.0006308474,"threshold_uncertainty_score":0.011815488},"labels":[],"label_agreement":null},{"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.014646296012564404,"score_gpt":0.2505833551941164,"score_spread":0.235937059181552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104744926","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049098965,0.00046862333,0.94537634,0.00043130858,0.000063140404,0.000049541984,0.000031664444,0.0002080634,0.004272328],"genre_scores_gemma":[0.68301475,0.00045894043,0.31108746,0.00007586681,0.000057781246,0.00020725974,0.000093334595,0.000067561756,0.004937028],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971837,0.00012577623,0.000013662278,0.00003327352,0.0000923587,0.000016487982],"domain_scores_gemma":[0.9989458,0.0007043786,0.000119292185,0.00007963005,0.000117877324,0.000033005374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006827449,0.00048244942,0.0006257235,0.00025327055,0.00038722059,0.00063005066,0.00045171715,0.00079739874,0.0016228635],"category_scores_gemma":[0.003298101,0.0002617537,0.000274401,0.0003755204,0.0011667713,0.00077546044,0.00079193065,0.0007080403,0.00021630862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000187935,0.000015882548,0.00022176586,0.000044297285,0.000010964055,0.00002936395,0.000035694524,0.9655619,0.0015543748,0.023441473,0.0003150552,0.008750365],"study_design_scores_gemma":[0.000007713486,0.0000035280882,0.000028383032,0.0000016464252,8.327166e-7,0.0000033037131,0.0000044517624,0.9947514,0.0003136077,0.004669053,0.00021445272,0.0000016642099],"about_ca_topic_score_codex":0.00405905,"about_ca_topic_score_gemma":0.0027827146,"teacher_disagreement_score":0.00405905,"about_ca_system_score_codex":0.00048552177,"about_ca_system_score_gemma":0.00079534523,"threshold_uncertainty_score":0.0080708265},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.008644112826970859,"score_gpt":0.2754375070949733,"score_spread":0.2667933942680024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105813930","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061566844,0.0006811531,0.9890265,0.00047144314,0.00046634185,0.000049219852,0.000025419922,0.000174707,0.0029485153],"genre_scores_gemma":[0.14951056,0.0019662734,0.8400999,0.0005294788,0.0008597708,0.0002481636,0.00009356718,0.00038139836,0.0063109356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99905246,0.0003975318,0.00006134776,0.00011412495,0.00031162158,0.000062813604],"domain_scores_gemma":[0.9987656,0.00052425923,0.000094057,0.0003937391,0.00013155305,0.00009075616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017413642,0.0008672617,0.0008419445,0.00035781733,0.0004934994,0.00062433456,0.0009094073,0.0008567938,0.0030271297],"category_scores_gemma":[0.0032899743,0.000387261,0.0010097332,0.00048065014,0.001776164,0.0016232722,0.0024682318,0.0026125866,0.000779088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024645662,0.0001347778,0.0007492963,0.0008602576,0.000119784614,0.001054725,0.0008546773,0.08072479,0.07455769,0.64862347,0.012915596,0.17915848],"study_design_scores_gemma":[0.00008066903,0.00029558036,0.00056996127,0.00006147327,0.000061571016,0.00050682185,0.00006312233,0.62725204,0.032147236,0.29798877,0.040899638,0.00007314752],"about_ca_topic_score_codex":0.00055811676,"about_ca_topic_score_gemma":0.00093886757,"teacher_disagreement_score":0.0030271297,"about_ca_system_score_codex":0.00019803458,"about_ca_system_score_gemma":0.00065837364,"threshold_uncertainty_score":0.01012677},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.019942057817476946,"score_gpt":0.24856257842710666,"score_spread":0.22862052060962973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108510172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035886858,0.0007927933,0.9533575,0.00019597473,0.000044858523,0.000068853464,0.000022722228,0.00026718067,0.009363231],"genre_scores_gemma":[0.52821916,0.0011414402,0.4606949,0.00012230477,0.000052403644,0.00028525692,0.000072309995,0.00025084685,0.009161339],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972826,0.00011499811,0.000017392345,0.000022027727,0.000095054165,0.000022209388],"domain_scores_gemma":[0.99940455,0.0002857445,0.00005650335,0.000087801345,0.0001367494,0.000028646744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008740449,0.00058843294,0.00053228,0.0005929202,0.00045247865,0.0007234625,0.0007106084,0.0006682879,0.0028845486],"category_scores_gemma":[0.001873315,0.00032468588,0.00046909612,0.00040929095,0.0010291992,0.00081278436,0.0012995852,0.0007571522,0.0008928848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014660203,0.00014832956,0.00048045904,0.00031756464,0.00006287591,0.00012992148,0.0003312394,0.66952395,0.023889316,0.17604354,0.0016420224,0.12728424],"study_design_scores_gemma":[0.000010327021,0.00002676792,0.00003598522,0.00001565062,0.0000050820454,0.000015814114,0.00002455861,0.9809264,0.0028898618,0.014633415,0.0014091673,0.000006944014],"about_ca_topic_score_codex":0.0015315016,"about_ca_topic_score_gemma":0.0016885687,"teacher_disagreement_score":0.0028845486,"about_ca_system_score_codex":0.0003940426,"about_ca_system_score_gemma":0.000672407,"threshold_uncertainty_score":0.009649754},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.04170620897805142,"score_gpt":0.35198990765666077,"score_spread":0.31028369867860933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111507332","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055021853,0.00018527659,0.988602,0.00016009569,0.00009793978,0.000033865843,0.000051023468,0.00036150723,0.0050062006],"genre_scores_gemma":[0.3271456,0.0007927475,0.65677196,0.00027039094,0.00020071589,0.00025318962,0.00033732917,0.00040002447,0.013827971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99959284,0.00015363314,0.000020155723,0.00005848956,0.00014631062,0.00002860518],"domain_scores_gemma":[0.9995766,0.000119244985,0.000050670755,0.00008752433,0.00013967235,0.000026292806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005125419,0.00065678364,0.0006110484,0.00029874893,0.00032583415,0.0004881751,0.0005110652,0.00058120524,0.0040660035],"category_scores_gemma":[0.0016351786,0.00021948412,0.0005301946,0.0003006261,0.0006848635,0.00043460482,0.0009099633,0.0009818934,0.0015854962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016751472,0.000051116498,0.0007878319,0.00053466967,0.000060980678,0.0003504806,0.00019179174,0.6468144,0.046342686,0.12123012,0.01295063,0.17051777],"study_design_scores_gemma":[0.000009293209,0.00003373562,0.00013090804,0.000017345847,0.0000044277126,0.000042564196,0.000009816736,0.9742708,0.0054551107,0.011769871,0.008243883,0.000012269481],"about_ca_topic_score_codex":0.0018235536,"about_ca_topic_score_gemma":0.0019928757,"teacher_disagreement_score":0.0040660035,"about_ca_system_score_codex":0.00036543183,"about_ca_system_score_gemma":0.0010207716,"threshold_uncertainty_score":0.013602078},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.011515731695473921,"score_gpt":0.2890850281962522,"score_spread":0.2775692965007783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113559515","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004313064,0.000049788712,0.99374855,0.00006357515,0.000037258847,0.00003010642,0.00004966844,0.00034134946,0.0013666883],"genre_scores_gemma":[0.09740592,0.00011759304,0.89811945,0.000083883344,0.00004423842,0.00011375736,0.00027051597,0.00018138772,0.0036631613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993345,0.0001624411,0.00003198838,0.0000503901,0.00036650017,0.000054082444],"domain_scores_gemma":[0.9994987,0.00015320098,0.00004598533,0.00010521339,0.00015843462,0.000038438455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081947324,0.00042278628,0.0004443863,0.00036338772,0.00036375478,0.00036023546,0.0007250821,0.0005807984,0.003339217],"category_scores_gemma":[0.0016901499,0.0002330303,0.000532635,0.00052681216,0.00046219456,0.00063633005,0.0011435356,0.0010533425,0.0011503767],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001463263,0.00011182504,0.00089109,0.00044033641,0.000051708234,0.0002640591,0.0002961859,0.54127896,0.08913897,0.092240326,0.011313208,0.263827],"study_design_scores_gemma":[0.000020289961,0.000036186328,0.00022215467,0.0000069986877,0.0000047485833,0.000045920784,0.000013616088,0.98011357,0.006779769,0.0049539446,0.007793099,0.000009589777],"about_ca_topic_score_codex":0.0027124367,"about_ca_topic_score_gemma":0.0038463913,"teacher_disagreement_score":0.003339217,"about_ca_system_score_codex":0.00027984468,"about_ca_system_score_gemma":0.0009663353,"threshold_uncertainty_score":0.011170864},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.030861724529350744,"score_gpt":0.3294186889575105,"score_spread":0.2985569644281597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121096325","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014592138,0.00027747118,0.9826066,0.00009767866,0.000015203766,0.000073956304,0.000010122012,0.0001230353,0.002203887],"genre_scores_gemma":[0.3866964,0.00040228802,0.6093176,0.00011976366,0.000029811192,0.0002178488,0.000053390366,0.0001755605,0.002987275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986577,0.00044342384,0.00010559178,0.00010119067,0.00060122256,0.000090858586],"domain_scores_gemma":[0.99732,0.0014665258,0.00026578538,0.00035825017,0.00051371293,0.000075702315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028967243,0.00066626305,0.0007982004,0.0009916717,0.00039921864,0.0008370426,0.0016253979,0.00078325556,0.0017306966],"category_scores_gemma":[0.0068508014,0.00047851162,0.0006238531,0.00049619836,0.0013456066,0.00135493,0.0013081938,0.00086335355,0.00052606425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036360728,0.00031950395,0.0030176563,0.00043618708,0.00012483144,0.000176358,0.00040171156,0.49614394,0.04388254,0.1503967,0.0019363845,0.3028005],"study_design_scores_gemma":[0.000051267147,0.00012161099,0.00048749903,0.000036735473,0.00002287907,0.00007994633,0.000040859,0.96367323,0.01727381,0.01615769,0.002028184,0.00002638435],"about_ca_topic_score_codex":0.0024574625,"about_ca_topic_score_gemma":0.0019257235,"teacher_disagreement_score":0.0028967243,"about_ca_system_score_codex":0.0008500885,"about_ca_system_score_gemma":0.0010374899,"threshold_uncertainty_score":0.015319526},"labels":[],"label_agreement":null},{"id":"W2122266675","doi":"10.1002/nla.547","title":"An efficient linear programming solver for optimal filter synthesis","year":2007,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sun Microsystems; Intel Corporation","keywords":"Solver; Linear programming; Deconvolution; Mathematics; Linear system; Mathematical optimization; Filter (signal processing); Algorithm; Point (geometry); Block (permutation group theory); System of linear equations; Applied mathematics; Computer science","score_opus":0.011562888039975466,"score_gpt":0.2707725232927044,"score_spread":0.25920963525272894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122266675","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021293422,0.000051139996,0.9956879,0.00008404737,0.000013383519,0.000025417352,0.000035799763,0.00025273155,0.0017202046],"genre_scores_gemma":[0.09197761,0.00013392688,0.903076,0.000090208596,0.000035728703,0.00036010265,0.0001554191,0.00023974731,0.0039311433],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995524,0.00016939738,0.00001757674,0.000062900566,0.0001503858,0.00004721082],"domain_scores_gemma":[0.9989648,0.00079985335,0.0000471976,0.000039346156,0.00012394042,0.000024914762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011682983,0.0009229154,0.0011946082,0.00062346674,0.00045635807,0.0010737404,0.00076788815,0.0012609132,0.0073061455],"category_scores_gemma":[0.0030041859,0.0006967603,0.0006581295,0.00071506377,0.00071266975,0.0006774402,0.0009766672,0.0014972377,0.0014006858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007874923,0.00005735705,0.00016733445,0.00014773115,0.000030044737,0.00008846992,0.00007644913,0.86710715,0.0030524002,0.043862738,0.0028510068,0.082480475],"study_design_scores_gemma":[0.000017715838,0.000009528357,0.000009613616,0.000004865003,0.000002642026,0.0000068096747,0.0000071018185,0.99230605,0.0004698848,0.0063260165,0.0008374673,0.0000023173966],"about_ca_topic_score_codex":0.0038536533,"about_ca_topic_score_gemma":0.0041575585,"teacher_disagreement_score":0.0073061455,"about_ca_system_score_codex":0.00066147925,"about_ca_system_score_gemma":0.0021154003,"threshold_uncertainty_score":0.02444154},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.012424760643217217,"score_gpt":0.2608739387652651,"score_spread":0.2484491781220479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128985516","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031909823,0.000029554985,0.96586835,0.000067826135,0.000020654026,0.00002760058,0.000031275795,0.00028073366,0.0017641081],"genre_scores_gemma":[0.3289505,0.000069606154,0.6674333,0.00005424879,0.000023716771,0.000054538195,0.000171366,0.00013899231,0.003103709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997074,0.000059115344,0.000015814194,0.000043016145,0.00014418358,0.000030440478],"domain_scores_gemma":[0.9990595,0.0004561964,0.0001091366,0.000118807664,0.00020427587,0.000052205552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004908455,0.00049164874,0.0004534467,0.0006601863,0.00032866825,0.0005234308,0.00054209045,0.00033897525,0.0028597454],"category_scores_gemma":[0.0027287495,0.00027053512,0.0005069437,0.0003065238,0.00071348046,0.0008513611,0.0008608158,0.00067172456,0.00066895917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035198563,0.00014625805,0.003749196,0.0003627618,0.00006825108,0.0006997627,0.0006414152,0.40261734,0.12939452,0.15437523,0.006252195,0.3013411],"study_design_scores_gemma":[0.000020550126,0.0000766899,0.0004416083,0.000013792109,0.000007068263,0.00016935075,0.00006628779,0.9455926,0.018709175,0.031910416,0.0029757721,0.000016589514],"about_ca_topic_score_codex":0.0013699359,"about_ca_topic_score_gemma":0.0020333428,"teacher_disagreement_score":0.0028597454,"about_ca_system_score_codex":0.00030306613,"about_ca_system_score_gemma":0.0006427492,"threshold_uncertainty_score":0.009566784},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.0225620477831706,"score_gpt":0.26577950657403887,"score_spread":0.24321745879086826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141654299","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055645104,0.00013447905,0.99172455,0.0001505551,0.000075653115,0.00008397373,0.00005980415,0.00019924415,0.0020072435],"genre_scores_gemma":[0.22679774,0.00019263134,0.76817805,0.00025103817,0.00020270278,0.00046033063,0.00035493536,0.0004964715,0.0030661311],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9491579,0.035504855,0.0015781609,0.0055931457,0.0074116224,0.0007542794],"domain_scores_gemma":[0.89377284,0.06525161,0.0072344933,0.02185134,0.011079467,0.0008101544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03394126,0.0010312585,0.0015289802,0.002278949,0.0014065224,0.002864432,0.0038718362,0.0015819768,0.0067850845],"category_scores_gemma":[0.18082675,0.001071979,0.0015292873,0.0021144887,0.0041347495,0.0041769845,0.004491518,0.0035720803,0.0018691239],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049958273,0.00010233254,0.0024169984,0.00057261885,0.00037807712,0.00017687735,0.0005273888,0.1385725,0.008491914,0.5649142,0.0067289164,0.27661854],"study_design_scores_gemma":[0.00006596296,0.00026002916,0.0015878498,0.00014539759,0.00007695923,0.0003024404,0.00015407935,0.51072764,0.013271449,0.4605836,0.012739366,0.000085263964],"about_ca_topic_score_codex":0.0007257423,"about_ca_topic_score_gemma":0.00070551655,"teacher_disagreement_score":0.03394126,"about_ca_system_score_codex":0.0012359186,"about_ca_system_score_gemma":0.0016868792,"threshold_uncertainty_score":0.17950064},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.023181486069593273,"score_gpt":0.2715561412659055,"score_spread":0.24837465519631222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146675507","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013547835,0.000036115744,0.9977634,0.00005834773,0.000011311266,0.00003745796,0.000024373803,0.00015881215,0.00055538386],"genre_scores_gemma":[0.06221389,0.00008636663,0.9350207,0.00008371564,0.0000463366,0.00037517116,0.00022726688,0.00017731612,0.0017691901],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980515,0.0009493824,0.000092193986,0.00026966666,0.0005073383,0.00012993142],"domain_scores_gemma":[0.99540246,0.0031108132,0.00022350784,0.00042501997,0.00071373757,0.00012443087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029637348,0.0010305758,0.0012606573,0.0015961567,0.000987235,0.0013136076,0.0018784738,0.0014214172,0.008280056],"category_scores_gemma":[0.0122716855,0.00078313646,0.0010286925,0.0016991453,0.001394575,0.0014013821,0.002640403,0.0025014563,0.0019233713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016216007,0.00009288892,0.0005231108,0.00012852211,0.00007009785,0.00011143451,0.00016553306,0.6307506,0.0039901077,0.12652321,0.0049573467,0.23252505],"study_design_scores_gemma":[0.0000114114355,0.00001472011,0.00004780974,0.000006625117,0.0000027319204,0.00001390141,0.000007547823,0.98102415,0.00058774604,0.017335111,0.00093902386,0.000009289206],"about_ca_topic_score_codex":0.010208645,"about_ca_topic_score_gemma":0.011204579,"teacher_disagreement_score":0.010208645,"about_ca_system_score_codex":0.0014663949,"about_ca_system_score_gemma":0.0038865546,"threshold_uncertainty_score":0.02769959},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.02116604428217539,"score_gpt":0.23628030653393445,"score_spread":0.21511426225175906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154024134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028443197,0.0012057538,0.9474665,0.002124096,0.00018022498,0.00006027386,0.00021802649,0.00024240636,0.020059545],"genre_scores_gemma":[0.8547075,0.00220351,0.11215059,0.0006188501,0.00055934984,0.00044499032,0.00050744496,0.00019309996,0.02861459],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990075,0.0005075241,0.00004173141,0.00012249808,0.00023480492,0.00008595391],"domain_scores_gemma":[0.99606556,0.0027905828,0.00042590627,0.0002195428,0.00032815582,0.00017022486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025975916,0.0007394066,0.0006950516,0.0010725714,0.00077964837,0.0016156835,0.0011895485,0.0014479974,0.007996399],"category_scores_gemma":[0.010193936,0.0003182437,0.0010162775,0.00077310123,0.0023203106,0.0020346446,0.0017395058,0.0024698349,0.00091362384],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006799153,0.000009350522,0.00020939103,0.000028206121,0.000008356086,0.000050078597,0.00007839392,0.10903814,0.00018726315,0.88646626,0.0007321713,0.0031856403],"study_design_scores_gemma":[0.0000049047326,0.0000046301716,0.00005337873,0.0000076504575,0.000002862876,0.000016235252,0.000013085363,0.3928619,0.00006361889,0.6057338,0.001230851,0.000007047851],"about_ca_topic_score_codex":0.0035991147,"about_ca_topic_score_gemma":0.002278049,"teacher_disagreement_score":0.007996399,"about_ca_system_score_codex":0.0014964105,"about_ca_system_score_gemma":0.0008983463,"threshold_uncertainty_score":0.026750684},"labels":[],"label_agreement":null},{"id":"W2162069340","doi":"10.1002/nla.468","title":"Analysis of a novel preconditioner for a class of <i>p</i>‐level lower rank extracted systems","year":2006,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Preconditioner; Toeplitz matrix; Mathematics; Conjugate gradient method; Circulant matrix; Positive-definite matrix; Rank (graph theory); Matrix (chemical analysis); Convolution (computer science); Conjugate residual method; Applied mathematics; Coefficient matrix; Linear system; Combinatorics; Mathematical analysis; Algorithm; Pure mathematics; Eigenvalues and eigenvectors; Computer science; Gradient descent","score_opus":0.010424466624073552,"score_gpt":0.24218569892566855,"score_spread":0.23176123230159498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162069340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037117247,0.000050593633,0.9598872,0.00011235752,0.000027690525,0.00004912386,0.000042243104,0.0004040493,0.002309536],"genre_scores_gemma":[0.59962326,0.00013951497,0.395036,0.00010921663,0.00005074305,0.00017720576,0.00026406176,0.00018589079,0.0044140597],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945635,0.00014556973,0.000026242398,0.000056435678,0.00024387828,0.00007155336],"domain_scores_gemma":[0.9983581,0.0007603716,0.00020643354,0.0002535167,0.00032720913,0.00009434214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009870582,0.00041285972,0.00054630305,0.00023823896,0.00036608492,0.0006585383,0.00057371176,0.0008308926,0.004501161],"category_scores_gemma":[0.0033540446,0.00023488821,0.000476014,0.00021346624,0.0007620259,0.0006622466,0.0008137554,0.00088565046,0.0008468703],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035306887,0.00012980239,0.0011324238,0.00023990666,0.000059502832,0.00030868294,0.00015352284,0.79251486,0.07080421,0.07425666,0.0031776652,0.056869626],"study_design_scores_gemma":[0.000012881024,0.00003515307,0.000104271,0.0000030151848,0.000002297718,0.000016482121,0.0000044781027,0.9918829,0.0054844553,0.001909252,0.000540278,0.0000044412627],"about_ca_topic_score_codex":0.0010392372,"about_ca_topic_score_gemma":0.0009590435,"teacher_disagreement_score":0.004501161,"about_ca_system_score_codex":0.0003466179,"about_ca_system_score_gemma":0.00091454876,"threshold_uncertainty_score":0.015057921},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.017080964280070325,"score_gpt":0.23537497000156704,"score_spread":0.2182940057214967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163749311","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33146513,0.0007987376,0.6488269,0.0025197568,0.0002335352,0.00016034224,0.0005256482,0.00045476313,0.015015172],"genre_scores_gemma":[0.9875508,0.00018284451,0.0078549115,0.00009290575,0.000059731177,0.000055761022,0.00006356568,0.000015400803,0.004124135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893945,0.00029823984,0.00003807656,0.00019660499,0.0001897209,0.00033787717],"domain_scores_gemma":[0.9986406,0.000557915,0.00029608465,0.00008100243,0.00024746094,0.00017693655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013980191,0.00069970015,0.00111013,0.0005622633,0.0007471431,0.00180406,0.0015393595,0.0015295147,0.0020748314],"category_scores_gemma":[0.0030230684,0.0005041511,0.0007068952,0.0005887507,0.0014382825,0.0014488988,0.0008420355,0.0010534954,0.0002883633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016107017,0.00008372707,0.001061253,0.00004717838,0.000025914886,0.00024573412,0.00010142944,0.91316336,0.0026004817,0.07719268,0.0010554454,0.004261738],"study_design_scores_gemma":[0.000010996124,0.000012754243,0.00008124354,0.0000023639464,0.0000046222153,0.00000830544,0.000007744284,0.99566936,0.000114059796,0.0039593917,0.00012237692,0.000006834436],"about_ca_topic_score_codex":0.020533565,"about_ca_topic_score_gemma":0.005429685,"teacher_disagreement_score":0.020533565,"about_ca_system_score_codex":0.0026578028,"about_ca_system_score_gemma":0.0018215508,"threshold_uncertainty_score":0.04082811},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.04498031905365354,"score_gpt":0.3201237360138019,"score_spread":0.2751434169601484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165397333","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013011902,0.00019823965,0.9828834,0.00009396669,0.0000520508,0.000069500384,0.00010048319,0.0012118708,0.002378498],"genre_scores_gemma":[0.25089675,0.00051520957,0.7415125,0.00010437681,0.00008952402,0.00030890602,0.00037870448,0.00045883027,0.005735215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995639,0.00013534546,0.000026420665,0.000050397823,0.00018081817,0.000043141303],"domain_scores_gemma":[0.9994311,0.00018356857,0.00007219799,0.00013619286,0.00012890006,0.000047971695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007011406,0.00064028834,0.0005468576,0.00035486507,0.00033141603,0.00034394028,0.00075588265,0.0006858184,0.002344486],"category_scores_gemma":[0.0017255225,0.00027905498,0.0006382491,0.00034971404,0.0005343589,0.0005879323,0.0009330498,0.0011555969,0.0006987293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033315172,0.00012108919,0.0007550561,0.0002569907,0.00009151542,0.00019241904,0.00013648925,0.68253464,0.059054475,0.056873392,0.0074338405,0.1922169],"study_design_scores_gemma":[0.000026164878,0.000060253038,0.00013914515,0.0000070142983,0.000007216563,0.000027819131,0.0000042615707,0.9818211,0.008351644,0.004770487,0.0047718347,0.00001296134],"about_ca_topic_score_codex":0.002249971,"about_ca_topic_score_gemma":0.0016020302,"teacher_disagreement_score":0.002344486,"about_ca_system_score_codex":0.00020590176,"about_ca_system_score_gemma":0.0009084057,"threshold_uncertainty_score":0.007843077},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Perturbation (astronomy); Mathematics; Invertible matrix; Factorization; Applied mathematics; Combinatorics; Pure mathematics; Algorithm; Physics; Quantum mechanics","score_opus":0.016871562044017387,"score_gpt":0.21272173993302815,"score_spread":0.19585017788901077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166356498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011622202,0.0003814558,0.9820769,0.00035602585,0.00009622755,0.000030502744,0.000066517714,0.0001746462,0.005195493],"genre_scores_gemma":[0.73422486,0.0019601998,0.25187674,0.00071549247,0.00054632226,0.00026846325,0.00040030864,0.00050810823,0.009499446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99621683,0.0017416772,0.00010332434,0.00032359926,0.0013725958,0.00024194598],"domain_scores_gemma":[0.98747975,0.008227094,0.0008556325,0.0011841672,0.0019385931,0.00031469157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004502464,0.0013427646,0.00071438774,0.0011648623,0.0005087902,0.0013346488,0.00057605444,0.0006903306,0.0033138206],"category_scores_gemma":[0.01893734,0.00034564032,0.0006380599,0.0006046264,0.002813564,0.0024268737,0.0022695183,0.0024200561,0.0012696462],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005432234,0.00007864105,0.0013992178,0.00032010075,0.00010429242,0.00049109757,0.00031991946,0.41818902,0.03392775,0.47338498,0.005778699,0.06546305],"study_design_scores_gemma":[0.0000075139887,0.0000838025,0.0004621841,0.0000458612,0.000010723026,0.0001259972,0.000048754882,0.8673813,0.008149683,0.12125154,0.0023980197,0.00003455571],"about_ca_topic_score_codex":0.0013658558,"about_ca_topic_score_gemma":0.00044619796,"teacher_disagreement_score":0.004502464,"about_ca_system_score_codex":0.00091953744,"about_ca_system_score_gemma":0.0008336854,"threshold_uncertainty_score":0.023811579},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.009507974454374934,"score_gpt":0.26415630785386945,"score_spread":0.2546483333994945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170774163","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005964012,0.00073453627,0.98519933,0.00025006858,0.00015088166,0.000025484891,0.000048338683,0.00008250352,0.0075447885],"genre_scores_gemma":[0.49538517,0.00275445,0.48722968,0.0003332044,0.0008109494,0.0001429627,0.00026502338,0.00016726599,0.012911197],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994381,0.00024325016,0.000031896343,0.00007788991,0.00017361424,0.000035219306],"domain_scores_gemma":[0.99928206,0.00021393163,0.00006856649,0.00010949738,0.00027906097,0.00004686578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083248946,0.0007902386,0.00053683383,0.000637303,0.00025331212,0.0007534074,0.00047758565,0.00039280945,0.0036774273],"category_scores_gemma":[0.002433691,0.00021186112,0.000600369,0.0009794519,0.00086653937,0.00080911646,0.00111452,0.0011374967,0.0008185628],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033812667,0.000041555042,0.00036178424,0.00015428371,0.0000395424,0.00016475355,0.0001061535,0.08954181,0.004354047,0.8052554,0.0058585242,0.09408846],"study_design_scores_gemma":[0.000009227525,0.000035677116,0.00023022678,0.00002427973,0.000007395238,0.0001273127,0.00003581498,0.5285364,0.0011216714,0.46139497,0.008462345,0.000014583302],"about_ca_topic_score_codex":0.00072598923,"about_ca_topic_score_gemma":0.00070209784,"teacher_disagreement_score":0.0036774273,"about_ca_system_score_codex":0.0003081682,"about_ca_system_score_gemma":0.0004162155,"threshold_uncertainty_score":0.01230222},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.011276630321847815,"score_gpt":0.2477752979146314,"score_spread":0.2364986675927836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2336877474","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14537556,0.00011186163,0.84728074,0.00020286939,0.0000914233,0.000063172534,0.00012968022,0.00046100764,0.006283675],"genre_scores_gemma":[0.76450783,0.00007939697,0.23137413,0.00006334589,0.00004398005,0.000091694215,0.00016623388,0.000073822695,0.0035995452],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980396,0.00006930122,0.000009240286,0.000026223952,0.00006961434,0.000021591282],"domain_scores_gemma":[0.999703,0.00014179511,0.000037841302,0.0000397924,0.000055166358,0.000022320983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030682815,0.00033629138,0.00047263163,0.00017899196,0.0002330025,0.00045402,0.0004477205,0.00048854377,0.0019041328],"category_scores_gemma":[0.00084787916,0.00016212076,0.00025028313,0.00019788303,0.00047866348,0.00023025498,0.0005558427,0.0005507124,0.00024337646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018349118,0.000098904056,0.0010086708,0.00012480344,0.00002259561,0.0001343089,0.00013805895,0.87896335,0.044313915,0.026550785,0.0018077876,0.046653327],"study_design_scores_gemma":[0.000012815314,0.000025799558,0.000112177244,0.000002311629,0.0000018672675,0.000009168768,0.0000052802206,0.9953152,0.0025123542,0.0012542802,0.00074659014,0.0000022508775],"about_ca_topic_score_codex":0.0019856961,"about_ca_topic_score_gemma":0.0015088517,"teacher_disagreement_score":0.0019856961,"about_ca_system_score_codex":0.00022962579,"about_ca_system_score_gemma":0.0007117596,"threshold_uncertainty_score":0.0063699484},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.009549939276433841,"score_gpt":0.2723625157209429,"score_spread":0.26281257644450906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2338260032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07178549,0.00025605081,0.9158143,0.00037585062,0.000035320776,0.000048717342,0.000080776306,0.00013316835,0.011470341],"genre_scores_gemma":[0.8006534,0.00042628733,0.1925064,0.00014082328,0.000051635576,0.00024328507,0.0001773649,0.00028281158,0.0055179885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996767,0.00016187,0.0000104988985,0.00004286241,0.000072224626,0.0000358687],"domain_scores_gemma":[0.9985649,0.0008445921,0.00018600927,0.00009035038,0.00021050373,0.00010365651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017477018,0.001032474,0.00070880423,0.0007550447,0.00047062067,0.0011181772,0.0007352785,0.0009169788,0.0034627984],"category_scores_gemma":[0.0051354486,0.0005685377,0.00038260693,0.0003950459,0.0012634238,0.0012351043,0.00097385497,0.0009951276,0.00048978406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108891225,0.000060032133,0.00045872122,0.0001635649,0.000040254232,0.000104506675,0.0000954761,0.6485856,0.011581191,0.32458472,0.002370524,0.011846553],"study_design_scores_gemma":[0.0000064286896,0.000025425039,0.000091173,0.000013907558,0.0000035584899,0.00001213945,0.000013910663,0.95908654,0.0010086288,0.039382905,0.00034632703,0.000009052496],"about_ca_topic_score_codex":0.0010608223,"about_ca_topic_score_gemma":0.001042983,"teacher_disagreement_score":0.0034627984,"about_ca_system_score_codex":0.00085554266,"about_ca_system_score_gemma":0.0011810068,"threshold_uncertainty_score":0.011584163},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.02607809847944596,"score_gpt":0.3188376433450104,"score_spread":0.29275954486556444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605276264","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013534644,0.0000558658,0.98365605,0.00015720425,0.000029272296,0.000038583534,0.00004998054,0.00035033934,0.002128014],"genre_scores_gemma":[0.3204751,0.00007562795,0.6727248,0.00012303265,0.000035898564,0.00021321236,0.00024533374,0.00036089198,0.0057461616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997223,0.00009117899,0.000015363787,0.00004345567,0.000106572305,0.000021089056],"domain_scores_gemma":[0.9995559,0.00020203753,0.000049137936,0.00006364382,0.00009842805,0.000030940526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006053572,0.0004824722,0.00062113965,0.00050796935,0.00039056627,0.0006787854,0.00095783814,0.0015846858,0.0029662368],"category_scores_gemma":[0.0016364807,0.00036294042,0.00059028354,0.0004056656,0.00066173525,0.00053276453,0.0014198648,0.0010610638,0.000638711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080141835,0.000055409062,0.0005079816,0.00006862776,0.000027173459,0.00015266635,0.00013011988,0.91869503,0.016346619,0.02716745,0.001832828,0.034936],"study_design_scores_gemma":[0.000004903289,0.000004421375,0.000022870634,0.0000015895075,7.9036647e-7,0.000006333001,0.0000040940704,0.99748623,0.0006080261,0.0013803272,0.00047858604,0.0000017630928],"about_ca_topic_score_codex":0.0028606388,"about_ca_topic_score_gemma":0.0028528948,"teacher_disagreement_score":0.0029662368,"about_ca_system_score_codex":0.000534322,"about_ca_system_score_gemma":0.00096480263,"threshold_uncertainty_score":0.009923041},"labels":[],"label_agreement":null},{"id":"W2741505342","doi":"10.1002/nla.2115","title":"Composite‐grid multigrid for diffusion on the sphere","year":2017,"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Multigrid method; Grid; Discretization; Mathematics; Partial differential equation; Finite element method; Surface (topology); Applied mathematics; Laplace transform; Coupling (piping); Field (mathematics); Algorithm; Mathematical optimization; Computer science; Geometry; Mathematical analysis; Pure mathematics","score_opus":0.028362760675690452,"score_gpt":0.3072370678725068,"score_spread":0.2788743071968164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741505342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049421567,0.00029204253,0.9380665,0.00041034873,0.00012978059,0.000045479483,0.000116094954,0.00042266902,0.011095616],"genre_scores_gemma":[0.6379843,0.00026277662,0.35362116,0.00011328773,0.000042252144,0.00009103515,0.00030872427,0.000195271,0.0073812422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985766,0.000035420195,0.000006047465,0.000018462197,0.00006640926,0.000015969852],"domain_scores_gemma":[0.9996755,0.00012680623,0.000026093065,0.00005031748,0.00008532974,0.000035897505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030977387,0.00022764684,0.00037313413,0.00040194843,0.00026596617,0.0004563646,0.000374519,0.00042474893,0.002237409],"category_scores_gemma":[0.0010873134,0.00010402588,0.00046616947,0.00033013418,0.000500045,0.00035535562,0.000739277,0.00074293395,0.00044266807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010274569,0.00003761564,0.0010887071,0.00007697278,0.000020527748,0.00011401929,0.00014879003,0.8148266,0.012969174,0.13031015,0.0034666206,0.036838043],"study_design_scores_gemma":[0.000004521287,0.0000044491876,0.00006731672,0.0000023251782,6.2234875e-7,0.0000063712587,0.000006494034,0.99095005,0.0005717514,0.0069538294,0.0014304552,0.0000019776166],"about_ca_topic_score_codex":0.0050372556,"about_ca_topic_score_gemma":0.004768526,"teacher_disagreement_score":0.0050372556,"about_ca_system_score_codex":0.0005445672,"about_ca_system_score_gemma":0.000602821,"threshold_uncertainty_score":0.010015845},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.013857533789645021,"score_gpt":0.22456116861458858,"score_spread":0.21070363482494356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779052738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005992565,0.000045648125,0.99170893,0.000089139845,0.00003415944,0.00003215431,0.000040415587,0.00021745544,0.0018394714],"genre_scores_gemma":[0.12860228,0.00011628131,0.8637604,0.000103060804,0.000060942766,0.00015719542,0.0002493319,0.0003485189,0.0066019585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973077,0.000060935618,0.000016690357,0.000036460202,0.00012908291,0.000026052981],"domain_scores_gemma":[0.999471,0.00023173746,0.000039855928,0.000065868546,0.00015389742,0.000037517635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005160947,0.00055805163,0.0006137078,0.00054650404,0.00040898085,0.0007918804,0.0009689927,0.0010580553,0.0030264591],"category_scores_gemma":[0.0019331679,0.00039441636,0.0008875858,0.00062610826,0.0006121341,0.00075353484,0.0015961167,0.0013239898,0.00072353974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008359089,0.00010966134,0.0011127503,0.00015258415,0.00005468318,0.00023551814,0.0002597488,0.8021421,0.020390512,0.07763476,0.0047819857,0.09304216],"study_design_scores_gemma":[0.000009201659,0.0000064528967,0.000039217957,0.000003028112,0.0000021000196,0.0000135100145,0.000009424219,0.99361354,0.0009751416,0.0037088452,0.0016162125,0.0000032109149],"about_ca_topic_score_codex":0.0055644657,"about_ca_topic_score_gemma":0.0051686554,"teacher_disagreement_score":0.0055644657,"about_ca_system_score_codex":0.0005784183,"about_ca_system_score_gemma":0.0013498283,"threshold_uncertainty_score":0.011064112},"labels":[],"label_agreement":null},{"id":"W2790987616","doi":"10.1002/nla.2202","title":"Nonlinearly preconditioned L‐BFGS as an acceleration mechanism for alternating least squares with application to tensor decomposition","year":2018,"lang":"en","type":"preprint","venue":"Numerical Linear Algebra with Applications","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Broyden–Fletcher–Goldfarb–Shanno algorithm; Nonlinear system; Tensor (intrinsic definition); Acceleration; Nonlinear conjugate gradient method; Robustness (evolution); Mathematics; Conjugate gradient method; Quasi-Newton method; Applied mathematics; Mathematical optimization; Computer science; Newton's method; Geometry; Gradient descent; Physics; Artificial intelligence","score_opus":0.030350149289128103,"score_gpt":0.3549142863738016,"score_spread":0.3245641370846735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790987616","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042839544,0.00007387619,0.99347514,0.0001315262,0.000045156594,0.000019652774,0.000028500339,0.00041608774,0.001525981],"genre_scores_gemma":[0.15025611,0.00021954413,0.8435124,0.0001279996,0.00005945182,0.00013351897,0.00015422438,0.00045999995,0.0050766827],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995022,0.00018891251,0.000023944163,0.0000550433,0.00019306736,0.000036860696],"domain_scores_gemma":[0.99914324,0.00029185164,0.00008801712,0.00015069627,0.0002671977,0.000059003043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008265282,0.00084803795,0.00053073687,0.0004660142,0.00037730343,0.0005568322,0.00067109586,0.00070095324,0.0035586685],"category_scores_gemma":[0.003214013,0.00031635817,0.0005357379,0.00047762843,0.00086083706,0.000636016,0.0012013699,0.0013520271,0.0015768666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013299489,0.000055267257,0.0006101497,0.0001876788,0.000054603643,0.000120308185,0.00017227928,0.7529485,0.019026967,0.10700146,0.005333799,0.11435588],"study_design_scores_gemma":[0.0000073016236,0.0000096962995,0.000036568297,0.000005874253,0.0000024874266,0.000010010621,0.000005245388,0.9853774,0.0017812756,0.0107823005,0.0019768656,0.000005008765],"about_ca_topic_score_codex":0.0050791646,"about_ca_topic_score_gemma":0.005979162,"teacher_disagreement_score":0.0050791646,"about_ca_system_score_codex":0.00049232005,"about_ca_system_score_gemma":0.0011716562,"threshold_uncertainty_score":0.011904895},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.01966037727123458,"score_gpt":0.3040190220013343,"score_spread":0.2843586447300997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806424598","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08633382,0.00024332888,0.90944374,0.00018458387,0.000032566357,0.000043582593,0.000038759394,0.00015366243,0.0035260064],"genre_scores_gemma":[0.8453157,0.00040578202,0.1481326,0.000081001286,0.000049143448,0.00015989889,0.00013756595,0.00019419844,0.0055239666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997725,0.000098573575,0.000008282062,0.000016665095,0.00008152576,0.00002252509],"domain_scores_gemma":[0.999059,0.00046189246,0.00010846977,0.00007208025,0.00025549062,0.00004309966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009922246,0.00035214072,0.00036361866,0.00045515294,0.00025793214,0.0004570161,0.00045100937,0.0004544088,0.0015303319],"category_scores_gemma":[0.0020788517,0.00016557382,0.00043709288,0.0002266899,0.0005960092,0.0005617831,0.0005007297,0.0005969281,0.00029592493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015194292,0.000076967524,0.00094128633,0.00014618076,0.000030089763,0.00006939822,0.00021963236,0.8481712,0.0332758,0.08164148,0.0010366753,0.03423936],"study_design_scores_gemma":[0.0000031271163,0.0000096829635,0.00007611702,0.0000024874973,0.0000014522968,0.000003777314,0.00000736023,0.9972844,0.00097054103,0.0014201761,0.000218021,0.0000029167338],"about_ca_topic_score_codex":0.0018537183,"about_ca_topic_score_gemma":0.0008672515,"teacher_disagreement_score":0.0018537183,"about_ca_system_score_codex":0.00032117587,"about_ca_system_score_gemma":0.00048068448,"threshold_uncertainty_score":0.005247414},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.012678977756962645,"score_gpt":0.28310248324648124,"score_spread":0.2704235054895186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945154147","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04037754,0.0003869912,0.94929224,0.00024523772,0.00013131763,0.00007553785,0.0000941469,0.000976787,0.008420177],"genre_scores_gemma":[0.43686393,0.0002348672,0.5583903,0.00008028819,0.000051832318,0.00016372293,0.000306358,0.0003380551,0.0035706328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946564,0.00018870267,0.000024209865,0.000045997313,0.00023842335,0.000037118552],"domain_scores_gemma":[0.99902046,0.00044173482,0.00006407335,0.0001972584,0.00022828186,0.000048206097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085862406,0.00039693527,0.00056402094,0.00050280377,0.0004938332,0.00044669845,0.00067480345,0.00042206526,0.002461852],"category_scores_gemma":[0.0026432064,0.00016524403,0.0004999928,0.00065641163,0.0006880672,0.00048607282,0.0014281947,0.0008989122,0.0006234097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026357488,0.00009238787,0.0017530475,0.00020828907,0.000040562703,0.00011710954,0.00014125029,0.70597786,0.013337148,0.11581806,0.003958226,0.15829255],"study_design_scores_gemma":[0.000014445232,0.0000150397,0.000108576314,0.0000046282107,0.0000019145884,0.000014267956,0.000007154639,0.985797,0.0017148046,0.01004984,0.0022675477,0.0000047259523],"about_ca_topic_score_codex":0.0022283716,"about_ca_topic_score_gemma":0.001922943,"teacher_disagreement_score":0.002461852,"about_ca_system_score_codex":0.00058847835,"about_ca_system_score_gemma":0.0008107052,"threshold_uncertainty_score":0.008235693},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.0241027217736144,"score_gpt":0.2951315000422264,"score_spread":0.271028778268612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945974182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0701269,0.00023861683,0.91456234,0.00059499947,0.00010320296,0.00009535188,0.000079089,0.00024376813,0.013955739],"genre_scores_gemma":[0.8318714,0.00038260053,0.15667959,0.00014560332,0.000103728555,0.0002840606,0.00019908279,0.00036385405,0.009970015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931514,0.0002456366,0.000030740215,0.00004746983,0.00029935266,0.000061664134],"domain_scores_gemma":[0.997068,0.0015042701,0.00021097781,0.000265942,0.0008536547,0.000097167365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020551328,0.0006087329,0.0005846886,0.0009335864,0.00048270728,0.00083542656,0.0006793487,0.00053316884,0.0027171217],"category_scores_gemma":[0.0058676074,0.0001861521,0.00077372027,0.00028853683,0.001555091,0.0007459984,0.0016859294,0.001119991,0.00037877797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001562338,0.00008788629,0.00161714,0.000157784,0.000048524867,0.00011826563,0.00025426896,0.7400946,0.008610308,0.22855927,0.0014051351,0.018890597],"study_design_scores_gemma":[0.00000393755,0.0000089754,0.00007234618,0.0000037688599,0.0000020844632,0.0000066162406,0.000011907461,0.9843277,0.00063988526,0.0145073095,0.00041294008,0.000002452428],"about_ca_topic_score_codex":0.0034999794,"about_ca_topic_score_gemma":0.0012783117,"teacher_disagreement_score":0.0034999794,"about_ca_system_score_codex":0.0006792697,"about_ca_system_score_gemma":0.00076422974,"threshold_uncertainty_score":0.010868728},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.019395089764698913,"score_gpt":0.28877605997942274,"score_spread":0.26938097021472385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963626304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049614203,0.000057821322,0.99281245,0.00012666052,0.000039253926,0.00003596129,0.000029614708,0.00048617265,0.0014507736],"genre_scores_gemma":[0.107049845,0.00012026452,0.88813365,0.00009887305,0.000055174707,0.000121934594,0.0002160515,0.00031942496,0.0038847327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993734,0.00022022336,0.00003991072,0.0001045149,0.00019130454,0.00007071319],"domain_scores_gemma":[0.9989557,0.00040056696,0.00009674492,0.00017188504,0.00030066472,0.000074472344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009164944,0.00093784294,0.00073643343,0.00049391703,0.00046240562,0.00087835785,0.000976389,0.0009052016,0.004719144],"category_scores_gemma":[0.0028596325,0.0003501706,0.00078026,0.0005788427,0.0009303245,0.00073370576,0.00126691,0.0016009657,0.002123911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021657735,0.00011315697,0.0010693215,0.00019748199,0.000059183607,0.0001817732,0.00020290956,0.6603172,0.017067391,0.06990583,0.010650511,0.24001874],"study_design_scores_gemma":[0.000009691052,0.000017578745,0.00005269067,0.0000045250176,0.000002278416,0.00001873712,0.0000075465705,0.99294794,0.001641512,0.004119522,0.0011723563,0.0000056896315],"about_ca_topic_score_codex":0.0064779683,"about_ca_topic_score_gemma":0.0059862263,"teacher_disagreement_score":0.0064779683,"about_ca_system_score_codex":0.00062531955,"about_ca_system_score_gemma":0.0019881157,"threshold_uncertainty_score":0.015787065},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.034105986348677286,"score_gpt":0.31636636466945295,"score_spread":0.28226037832077566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970518087","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08776328,0.00034656064,0.9038283,0.00025150072,0.000057040274,0.000036758283,0.00003249886,0.0001729695,0.007510988],"genre_scores_gemma":[0.8612633,0.00036904454,0.13021815,0.00010852825,0.00008051423,0.00010074814,0.00007129426,0.00022461597,0.007563721],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997396,0.00010415521,0.0000072037888,0.000026878588,0.000093906965,0.000028324623],"domain_scores_gemma":[0.9993297,0.00035408363,0.00007335248,0.000058573176,0.00015028878,0.000033989254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073523715,0.0004119704,0.00028948387,0.0004520413,0.00029535248,0.0006502703,0.0005320239,0.00042926677,0.0017920571],"category_scores_gemma":[0.0020225334,0.00016754039,0.0004689946,0.0001693602,0.000753196,0.0007523065,0.00078530406,0.0009296382,0.00037360183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015374244,0.00009894497,0.0011163128,0.00017220585,0.000035633406,0.0001322512,0.00027401815,0.6814913,0.059049413,0.20022522,0.0017292248,0.05552179],"study_design_scores_gemma":[0.000002850963,0.000016798665,0.000100123194,0.000004746508,0.000002559968,0.000013327866,0.000017616892,0.99280214,0.0020920262,0.0044367453,0.00050594815,0.000005128006],"about_ca_topic_score_codex":0.0011974986,"about_ca_topic_score_gemma":0.0008309445,"teacher_disagreement_score":0.0017920571,"about_ca_system_score_codex":0.00031516814,"about_ca_system_score_gemma":0.00033039358,"threshold_uncertainty_score":0.0059949756},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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)","score_opus":0.03470059674419496,"score_gpt":0.3201134359785043,"score_spread":0.2854128392343093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988137070","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0125349695,0.00016181065,0.9842743,0.00012550829,0.00007000534,0.000028332579,0.00003149261,0.0011282756,0.0016452676],"genre_scores_gemma":[0.23480758,0.00022910394,0.75794184,0.00014707143,0.00006148503,0.00014685084,0.00022159758,0.0004971687,0.0059472546],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999371,0.0001911365,0.00003768373,0.00008667742,0.00026349633,0.000050008177],"domain_scores_gemma":[0.9987179,0.00040611782,0.00013739547,0.00024218172,0.00042178275,0.00007459177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010353856,0.0010450204,0.0005439444,0.00048143422,0.00041912816,0.0005940571,0.0009692596,0.0006874897,0.0026528512],"category_scores_gemma":[0.0041664303,0.0004007327,0.00055543357,0.00043758444,0.0005775771,0.0008500974,0.0010001494,0.0012367583,0.0013073487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028975235,0.00008893152,0.002175408,0.00017739102,0.00010673483,0.00016761507,0.00023154935,0.5511095,0.02858108,0.038243324,0.007709098,0.37111968],"study_design_scores_gemma":[0.0000069237026,0.000017336095,0.00012646765,0.000005397783,0.0000029578764,0.000015769512,0.0000054328284,0.99338645,0.0031402525,0.0018892003,0.0013964874,0.000007319404],"about_ca_topic_score_codex":0.004962014,"about_ca_topic_score_gemma":0.0067310915,"teacher_disagreement_score":0.004962014,"about_ca_system_score_codex":0.0004515206,"about_ca_system_score_gemma":0.0010780622,"threshold_uncertainty_score":0.009866297},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.037532764155874566,"score_gpt":0.30650913640149274,"score_spread":0.26897637224561816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006898615","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04480457,0.00006790468,0.95118016,0.00018833742,0.00003613558,0.00003055923,0.000024059827,0.00031776712,0.0033504742],"genre_scores_gemma":[0.7353993,0.00011314538,0.25991568,0.000086145534,0.000030339586,0.00011216536,0.00009408707,0.00036489344,0.0038842207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997098,0.000101651654,0.000012924644,0.00002149786,0.00012613383,0.000028107677],"domain_scores_gemma":[0.99866414,0.0006561711,0.000098677316,0.00022215783,0.00031400737,0.000044774322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010837509,0.00030791768,0.00029296952,0.0006143285,0.00042600697,0.00069671386,0.0004375521,0.00044141887,0.0022591506],"category_scores_gemma":[0.0029789757,0.00016395892,0.0004923766,0.00027936004,0.0006777698,0.0007762641,0.0006317132,0.0009177348,0.00042939465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001424071,0.00012330372,0.0025547165,0.00014382914,0.00003645571,0.00014263965,0.0004468123,0.7181607,0.03936058,0.14829418,0.002176189,0.08841819],"study_design_scores_gemma":[0.0000018091628,0.000004386225,0.0001254439,0.0000024959709,7.6055466e-7,0.0000048679744,0.000008375494,0.9954579,0.001311716,0.0026968531,0.0003825329,0.0000027898311],"about_ca_topic_score_codex":0.0025066375,"about_ca_topic_score_gemma":0.0019595518,"teacher_disagreement_score":0.0025066375,"about_ca_system_score_codex":0.0004956295,"about_ca_system_score_gemma":0.0005691105,"threshold_uncertainty_score":0.0075576305},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.04017474802119845,"score_gpt":0.3171565609560845,"score_spread":0.27698181293488605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092221604","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01616641,0.00025156318,0.9807767,0.00034041575,0.000056938385,0.000020096006,0.00001430367,0.00011000383,0.0022635644],"genre_scores_gemma":[0.63489085,0.00050581445,0.3580291,0.00019930008,0.00013456284,0.000121474215,0.00006995363,0.00026255992,0.0057863197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989427,0.0005721984,0.000026820866,0.00010679736,0.00028623088,0.000065242275],"domain_scores_gemma":[0.9972474,0.0018405458,0.00021094416,0.0002856228,0.0003346898,0.00008085911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026196912,0.0008186459,0.0010111358,0.00047941966,0.0003467749,0.0013523367,0.00071788917,0.0008510525,0.0017472984],"category_scores_gemma":[0.009643325,0.00040881286,0.00038216656,0.00062962866,0.0017071035,0.0012163913,0.0013881895,0.0014706594,0.0004660195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110512236,0.000028027487,0.00025068785,0.00010196246,0.00003527881,0.000053823016,0.000058405327,0.8590746,0.0037811012,0.103545606,0.001602756,0.03135725],"study_design_scores_gemma":[0.0000066282923,0.000019119261,0.000034995883,0.0000048426054,0.0000019805311,0.0000068307836,0.0000034395327,0.98491955,0.0008862377,0.013771449,0.00034109165,0.0000038585504],"about_ca_topic_score_codex":0.0016035403,"about_ca_topic_score_gemma":0.0012856268,"teacher_disagreement_score":0.0026196912,"about_ca_system_score_codex":0.00079295837,"about_ca_system_score_gemma":0.0010651422,"threshold_uncertainty_score":0.013854444},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.015482306554258552,"score_gpt":0.28666895587730923,"score_spread":0.2711866493230507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135361124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19230685,0.00024688017,0.79686886,0.00035196432,0.00010201032,0.000093470146,0.00006315556,0.0007788938,0.009187945],"genre_scores_gemma":[0.73651826,0.000092948474,0.26031905,0.000072349,0.00001725514,0.00008604087,0.00009527635,0.0002903038,0.0025085441],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996799,0.00011042117,0.000012762798,0.000037834146,0.000112871036,0.000046179313],"domain_scores_gemma":[0.9990343,0.0005046953,0.000103950304,0.00014234171,0.00016137322,0.00005330245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008412011,0.00051740586,0.00035026608,0.0003022873,0.00028281385,0.0005937022,0.00065460365,0.00049615157,0.0016487711],"category_scores_gemma":[0.0023387915,0.00016574172,0.00032585528,0.0002445371,0.00071270304,0.00050562306,0.00082965835,0.0009009659,0.0003364429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017320138,0.00015796175,0.0011730681,0.00009874526,0.000024073717,0.000081192105,0.000080857586,0.9203528,0.018805685,0.021462781,0.0012056349,0.03638414],"study_design_scores_gemma":[0.000008501469,0.000019309113,0.000055823242,0.0000016306,0.0000012030516,0.0000038125197,0.0000071220593,0.99632984,0.0023804803,0.0009213181,0.00026860525,0.0000022747606],"about_ca_topic_score_codex":0.0034924638,"about_ca_topic_score_gemma":0.0035819856,"teacher_disagreement_score":0.0034924638,"about_ca_system_score_codex":0.00052116835,"about_ca_system_score_gemma":0.00096341514,"threshold_uncertainty_score":0},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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)","score_opus":0.01827425167728905,"score_gpt":0.28514586803453845,"score_spread":0.26687161635724943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137409987","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06031263,0.0001784475,0.9234053,0.00036404433,0.00019711842,0.000057818786,0.000087085566,0.0005893069,0.0148082385],"genre_scores_gemma":[0.7104074,0.00026341894,0.28063992,0.00019469514,0.00013764382,0.00010839009,0.00022366377,0.00026599807,0.007758916],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992404,0.00027547314,0.000034183202,0.00007742545,0.00029864055,0.00007385114],"domain_scores_gemma":[0.9990397,0.0003536612,0.0001247088,0.0002091543,0.00021093366,0.00006181693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006835926,0.0005322942,0.0005719638,0.0004536605,0.00036190992,0.000821903,0.000483047,0.0006001207,0.004473376],"category_scores_gemma":[0.0026666552,0.00020614495,0.00042133202,0.0003144964,0.0012473767,0.00066374196,0.0013934864,0.0010930529,0.00092551095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015550187,0.00007696968,0.0010887361,0.00020433708,0.00003304728,0.00017313738,0.00022559016,0.61308795,0.062605225,0.2527141,0.0044546234,0.06518073],"study_design_scores_gemma":[0.00001432562,0.000028565477,0.00016866486,0.0000079750735,0.0000025761353,0.00002085109,0.000011455535,0.97043985,0.010028999,0.015823014,0.0034475492,0.0000062870545],"about_ca_topic_score_codex":0.0016427829,"about_ca_topic_score_gemma":0.0014419594,"teacher_disagreement_score":0.004473376,"about_ca_system_score_codex":0.00041138017,"about_ca_system_score_gemma":0.00085574127,"threshold_uncertainty_score":0.014964998},"labels":[],"label_agreement":null},{"id":"W3158295436","doi":"10.1002/nla.2388","title":"Independence of placement for local Fourier analysis","year":2021,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Discretization; Multigrid method; Simple (philosophy); Representation (politics); Degrees of freedom (physics and chemistry); Operator (biology); Grid; Transfer operator; Applied mathematics; Partial differential equation; Mathematical optimization; Mathematical analysis; Geometry","score_opus":0.01588623537346656,"score_gpt":0.2975203733635784,"score_spread":0.28163413799011183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158295436","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022061935,0.00014412873,0.9576994,0.00030221295,0.00023829438,0.000040330928,0.00006464112,0.00036923774,0.019079812],"genre_scores_gemma":[0.72832483,0.00050245965,0.25491223,0.00049352803,0.00044052282,0.00019302005,0.00019524782,0.0008442388,0.014093864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988451,0.00039284397,0.00005520514,0.00020322949,0.00039707273,0.00010646234],"domain_scores_gemma":[0.9980325,0.0006708487,0.00021551145,0.00059372373,0.00035477182,0.00013263809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010871144,0.0007173113,0.00049392035,0.000604167,0.0005819286,0.0017838556,0.00085036876,0.0009865415,0.007295892],"category_scores_gemma":[0.0058108233,0.0002639616,0.00066332234,0.00042854677,0.0022068059,0.0021721595,0.002367458,0.0018500878,0.0025138382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010065573,0.000075361706,0.0005086593,0.00009915126,0.000011919042,0.00022776588,0.00016475838,0.02708189,0.021636158,0.8907856,0.003957942,0.05535012],"study_design_scores_gemma":[0.000032506054,0.00011749577,0.0004649637,0.00005656363,0.000012790728,0.0003514483,0.00010292219,0.46503982,0.016884737,0.50242865,0.014466107,0.000041998057],"about_ca_topic_score_codex":0.00038856882,"about_ca_topic_score_gemma":0.00028970835,"teacher_disagreement_score":0.007295892,"about_ca_system_score_codex":0.00046084987,"about_ca_system_score_gemma":0.00050193607,"threshold_uncertainty_score":0.024407268},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.016190170580138406,"score_gpt":0.2607405617680234,"score_spread":0.244550391187885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183856668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047104962,0.0001221925,0.9470642,0.00014956383,0.000112248046,0.000039849598,0.0000692027,0.00041484772,0.0049229073],"genre_scores_gemma":[0.58194023,0.0002067009,0.4099239,0.000074810014,0.000075285236,0.00011831273,0.0002120105,0.00016495009,0.00728379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99986804,0.00003393817,0.000007775584,0.000014486984,0.00005236812,0.000023424986],"domain_scores_gemma":[0.9997427,0.00009369722,0.000023460676,0.00003635616,0.00007344812,0.000030361649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033421358,0.0003449293,0.0005520712,0.00026052006,0.0002523036,0.00033951763,0.0003757372,0.00045459383,0.0025677616],"category_scores_gemma":[0.00087766815,0.00013268112,0.0002885503,0.00024729676,0.00045805893,0.0003678253,0.00062246836,0.000707666,0.00041780178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027978938,0.00015767998,0.0013370281,0.00039683792,0.000063249354,0.00029200665,0.00023323533,0.6888878,0.093371116,0.059545502,0.003433771,0.15200202],"study_design_scores_gemma":[0.0000101481755,0.000035122554,0.00014613061,0.000006210973,0.0000032342082,0.00002118972,0.000008891541,0.9888362,0.007426728,0.0018646724,0.0016369886,0.0000044610833],"about_ca_topic_score_codex":0.0021903745,"about_ca_topic_score_gemma":0.0024503784,"teacher_disagreement_score":0.0025677616,"about_ca_system_score_codex":0.00027506924,"about_ca_system_score_gemma":0.0007445737,"threshold_uncertainty_score":0.008590043},"labels":[],"label_agreement":null},{"id":"W4243141097","doi":"10.1002/1099-1506(200010/12)7:7/8<489::aid-nla208>3.0.co;2-w","title":"Editorial","year":2000,"lang":"en","type":"editorial","venue":"Numerical Linear Algebra with Applications","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Applied mathematics; Calculus (dental); Orthodontics; Medicine","score_opus":0.02443248650506864,"score_gpt":0.36559506042489415,"score_spread":0.3411625739198255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243141097","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000029890274,0.0063589755,0.00010905791,0.0250124,0.96169525,0.00002700413,0.00010143217,0.0000545151,0.0066114618],"genre_scores_gemma":[0.0009458502,0.01370976,0.00019057638,0.030496217,0.8886595,0.000059956197,0.00018097348,0.00008054741,0.06567669],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99801046,0.0003024253,0.00024512742,0.00031147114,0.0009926372,0.00013804785],"domain_scores_gemma":[0.99067664,0.0022849087,0.00052174245,0.00033237535,0.004716779,0.0014675057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035518915,0.0026097826,0.002052496,0.002976385,0.0021007243,0.0061754268,0.0021445123,0.0063164863,0.03727331],"category_scores_gemma":[0.017079378,0.000740434,0.0013200213,0.0013214351,0.0013125989,0.0036028754,0.0009825928,0.008763773,0.03302291],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010677963,0.0000027834124,0.000007507155,0.00005651045,0.000002467997,0.000032987944,0.0000028197455,0.000009019744,0.000011541898,0.00013551822,0.99620026,0.0035278166],"study_design_scores_gemma":[0.000016569456,0.0000061904143,0.00008734185,0.00021468857,0.000009147112,0.00010222092,0.000012953799,0.000038706406,0.00003612495,0.00041536865,0.9990558,0.000004889023],"about_ca_topic_score_codex":0.0019411441,"about_ca_topic_score_gemma":0.004647937,"teacher_disagreement_score":0.03727331,"about_ca_system_score_codex":0.0022686536,"about_ca_system_score_gemma":0.0025228518,"threshold_uncertainty_score":0},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.01661374818348609,"score_gpt":0.2450198333137332,"score_spread":0.2284060851302471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253510993","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15809013,0.0042273365,0.78506106,0.0033004596,0.0006380026,0.0001247787,0.00018981026,0.0008170773,0.047551382],"genre_scores_gemma":[0.88428676,0.0037052487,0.08714555,0.00088215433,0.0007027683,0.0002668326,0.00035158475,0.0005959399,0.022063116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976393,0.0009304945,0.00006528758,0.00019396018,0.0007925316,0.00037849107],"domain_scores_gemma":[0.9761752,0.017775824,0.001149991,0.001448279,0.0024572946,0.0009935505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004600713,0.001612219,0.0009940545,0.0018098096,0.0014849748,0.0018792051,0.0011855746,0.0015602792,0.006416315],"category_scores_gemma":[0.03267874,0.00045278826,0.00073134416,0.0013051212,0.005008751,0.004897421,0.003160141,0.0031857418,0.0020681974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003950225,0.000082117454,0.0021377841,0.00024827398,0.00003978635,0.0004223321,0.0004497728,0.054869946,0.0063258866,0.8826679,0.009374245,0.042986993],"study_design_scores_gemma":[0.000040984643,0.00011497572,0.00054176274,0.0001022589,0.000022528153,0.0003709684,0.00011582281,0.33622426,0.0059674657,0.65116245,0.005264387,0.00007214779],"about_ca_topic_score_codex":0.0023401757,"about_ca_topic_score_gemma":0.0021456848,"teacher_disagreement_score":0.006416315,"about_ca_system_score_codex":0.0014697326,"about_ca_system_score_gemma":0.0012133595,"threshold_uncertainty_score":0.024331212},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.03566184032007813,"score_gpt":0.29838171194535634,"score_spread":0.2627198716252782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366774998","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072117276,0.00007890067,0.9912875,0.00009069122,0.000055421835,0.000024543899,0.000011805911,0.000120034,0.0011193089],"genre_scores_gemma":[0.36259595,0.00029317665,0.6295881,0.00019415937,0.00008575675,0.00017353932,0.000092437775,0.00038020054,0.006596573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942964,0.00015511163,0.000024891508,0.000080380574,0.0002555832,0.00005433052],"domain_scores_gemma":[0.9986524,0.00061149115,0.00009135291,0.00015386408,0.0004094575,0.000081572936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020367943,0.000570429,0.00055890833,0.0006017232,0.0005398734,0.0010748355,0.0010593276,0.0012269567,0.0031039892],"category_scores_gemma":[0.0054568336,0.00033887426,0.0007152696,0.00042052908,0.0010621055,0.0011450743,0.0012599996,0.0013069236,0.0006626791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022691362,0.00016798264,0.0015055492,0.0002719748,0.000082809616,0.00017430207,0.00038019873,0.45988467,0.041249137,0.3744731,0.0031431697,0.11844021],"study_design_scores_gemma":[0.0000072085963,0.000018519151,0.000075127115,0.000010941429,0.0000060383118,0.000018793247,0.000012726727,0.9872366,0.0019662275,0.009216512,0.0014218849,0.000009373814],"about_ca_topic_score_codex":0.0029286277,"about_ca_topic_score_gemma":0.003224962,"teacher_disagreement_score":0.0031039892,"about_ca_system_score_codex":0.0007842806,"about_ca_system_score_gemma":0.0012418843,"threshold_uncertainty_score":0.010771751},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.0439613445610292,"score_gpt":0.2994658209317939,"score_spread":0.25550447637076473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379648388","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054674014,0.00034352523,0.94067556,0.00024739405,0.00006566321,0.00005081299,0.000050242124,0.00012048495,0.003772284],"genre_scores_gemma":[0.6046099,0.00029959242,0.38916838,0.00012319203,0.000047243044,0.00022183724,0.00018536186,0.00019702221,0.0051475093],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997328,0.00010908837,0.000011135663,0.00003631096,0.00007710128,0.000033657365],"domain_scores_gemma":[0.99967515,0.00014799918,0.00004654927,0.000041626736,0.00006201294,0.000026629425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005912182,0.0005805234,0.0006918612,0.00045905134,0.00039341894,0.00065359,0.00095118204,0.0010255914,0.0010328615],"category_scores_gemma":[0.0012579473,0.00036893485,0.00072513154,0.00035297545,0.00078921136,0.0006839572,0.0009313541,0.0010816534,0.00024961968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006378008,0.000052699394,0.00045344277,0.00010938308,0.000034706998,0.000057802234,0.00009940522,0.9374217,0.014546441,0.02903806,0.0005612104,0.017561331],"study_design_scores_gemma":[0.0000050832655,0.000009349984,0.00003850002,0.0000031844347,0.0000017014777,0.000005558304,0.0000063952566,0.99770087,0.0006824318,0.00111614,0.00042651314,0.000004317939],"about_ca_topic_score_codex":0.005807992,"about_ca_topic_score_gemma":0.004078847,"teacher_disagreement_score":0.005807992,"about_ca_system_score_codex":0.0005148854,"about_ca_system_score_gemma":0.001009786,"threshold_uncertainty_score":0.0115484},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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)","score_opus":0.07422935551257316,"score_gpt":0.2880792033795224,"score_spread":0.21384984786694927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385694302","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29007232,0.0007209216,0.70114464,0.0015282817,0.00017738203,0.000095867625,0.00015810409,0.00044676248,0.005655727],"genre_scores_gemma":[0.9552739,0.00025605224,0.04288742,0.00017587272,0.00005137328,0.000076572986,0.00015608945,0.00023367176,0.00088909315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972722,0.0014877666,0.00015155894,0.0003282915,0.00050210586,0.00025810048],"domain_scores_gemma":[0.9623948,0.030294897,0.0024494496,0.0018247955,0.0024863626,0.0005498184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075073186,0.00085888547,0.0010265132,0.0005459709,0.0009291295,0.0017533997,0.0008078049,0.0013675973,0.0014454287],"category_scores_gemma":[0.036047358,0.00085292454,0.00075251766,0.00040019237,0.0026096262,0.0018567877,0.0023198526,0.002347355,0.00018257313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001449977,0.00004144523,0.004137908,0.00007158451,0.000067103356,0.00014507999,0.00013136856,0.96085566,0.004330517,0.022915117,0.0005515916,0.0066076936],"study_design_scores_gemma":[0.000009083567,0.000014138376,0.00048076644,0.00001061599,0.000005350991,0.000007688823,0.000010545336,0.9946725,0.0014054974,0.0032597054,0.00011510309,0.000009092313],"about_ca_topic_score_codex":0.011858735,"about_ca_topic_score_gemma":0.004650095,"teacher_disagreement_score":0.011858735,"about_ca_system_score_codex":0.0010391863,"about_ca_system_score_gemma":0.0021163921,"threshold_uncertainty_score":0.03970301},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.01617655189294508,"score_gpt":0.2601246523332715,"score_spread":0.2439481004403264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389941500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008733402,0.000084608815,0.9817886,0.00016568383,0.00009765646,0.00008103807,0.00004836347,0.00055177085,0.008448929],"genre_scores_gemma":[0.32589805,0.00028813383,0.663382,0.0003136038,0.00018740182,0.00027521403,0.00036277584,0.00072134205,0.008571534],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993311,0.00017374606,0.000025444822,0.00008820663,0.00033250378,0.000048939277],"domain_scores_gemma":[0.9991327,0.00027419775,0.000049673028,0.00026493508,0.00024142336,0.000037047845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008042656,0.0007144017,0.0007655111,0.0011710151,0.00044267738,0.00076987705,0.0012078569,0.0008377164,0.0034634038],"category_scores_gemma":[0.0032137458,0.00030952413,0.0010326703,0.00055547175,0.0012766885,0.00065570197,0.0028547675,0.0014924976,0.0012083108],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006789467,0.000073596566,0.0005667743,0.00013819388,0.00005039646,0.00009235075,0.00016845137,0.7487857,0.012436477,0.16710056,0.0033233974,0.067196235],"study_design_scores_gemma":[0.000006101628,0.00001179514,0.00003994197,0.0000046292744,0.0000025416796,0.000013798731,0.0000064543406,0.9754157,0.00093001995,0.020034742,0.003530643,0.00000360388],"about_ca_topic_score_codex":0.0031622583,"about_ca_topic_score_gemma":0.0029450045,"teacher_disagreement_score":0.0034634038,"about_ca_system_score_codex":0.000567703,"about_ca_system_score_gemma":0.00061896024,"threshold_uncertainty_score":0.0115863085},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.013279353579700478,"score_gpt":0.3005640920308566,"score_spread":0.2872847384511561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403584193","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01147304,0.00081996265,0.97432023,0.0013350731,0.00015667747,0.000030813015,0.0000337456,0.000116661,0.011713665],"genre_scores_gemma":[0.557551,0.002482857,0.4186666,0.0005934473,0.00057733763,0.000251187,0.00019602709,0.0006229342,0.019058637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992662,0.00030734943,0.000031483327,0.000063894186,0.00028270783,0.00004838323],"domain_scores_gemma":[0.997549,0.0014621468,0.00016375525,0.0002484025,0.0004978095,0.000078959725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022816882,0.0007492454,0.000584794,0.001227847,0.00045415421,0.001325956,0.0009757315,0.000992911,0.0030806402],"category_scores_gemma":[0.0052772975,0.00028943614,0.0010504363,0.00055777346,0.0022285518,0.001563336,0.0019485924,0.0029319087,0.0006672528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043800716,0.000060520088,0.00069077266,0.00018098761,0.000040075716,0.00013735774,0.0002413259,0.22341007,0.008691326,0.7348468,0.0029369502,0.02872006],"study_design_scores_gemma":[0.0000062800677,0.000014535378,0.00013374977,0.000018753433,0.0000037575319,0.000037372345,0.00002653566,0.8922259,0.0015946516,0.10239214,0.003536813,0.0000095229925],"about_ca_topic_score_codex":0.0020692833,"about_ca_topic_score_gemma":0.0008848277,"teacher_disagreement_score":0.0030806402,"about_ca_system_score_codex":0.0008176297,"about_ca_system_score_gemma":0.00079523865,"threshold_uncertainty_score":0.012066841},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.01797523011889221,"score_gpt":0.2937145160819113,"score_spread":0.2757392859630191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405384795","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020074844,0.000069920825,0.9971629,0.000072625015,0.00003424231,0.00001619607,0.000036554353,0.00009560727,0.00050436275],"genre_scores_gemma":[0.16294977,0.0005866671,0.8310306,0.00015286184,0.0001973429,0.00015884009,0.00058449636,0.00030303298,0.0040364806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910635,0.000330078,0.00005512255,0.00018306373,0.00026637697,0.000058957212],"domain_scores_gemma":[0.9986933,0.00034154078,0.00018691347,0.00023647687,0.00042343079,0.000118287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014324997,0.0012442808,0.00085745734,0.0008611172,0.00032449432,0.0009718965,0.00088589685,0.00058935455,0.0031012166],"category_scores_gemma":[0.0034096406,0.00030989735,0.0010551614,0.0009677971,0.0014329467,0.0014407467,0.0015927607,0.0018922106,0.0010515301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013525812,0.00009038336,0.00081753253,0.00037284332,0.00009141598,0.00020956121,0.00022983467,0.4636521,0.019211002,0.30787078,0.012971732,0.19434752],"study_design_scores_gemma":[0.000005794317,0.000025937958,0.0000843531,0.0000074322356,0.000004189465,0.000033473152,0.000015074216,0.97338957,0.0017460242,0.022758702,0.0019176161,0.000011790323],"about_ca_topic_score_codex":0.0044591115,"about_ca_topic_score_gemma":0.002327945,"teacher_disagreement_score":0.0044591115,"about_ca_system_score_codex":0.00055336487,"about_ca_system_score_gemma":0.0013790487,"threshold_uncertainty_score":0.010374665},"labels":[],"label_agreement":null},{"id":"W4410907582","doi":"10.1002/nla.70023","title":"Achieving h‐ and p‐Robust Monolithic Multigrid Solvers for the Stokes Equations","year":2025,"lang":"en","type":"article","venue":"Numerical Linear Algebra with Applications","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multigrid method; Mathematics; Applied mathematics; Computational science; Mathematical analysis; Partial differential equation","score_opus":0.022889541384707345,"score_gpt":0.2948772371208755,"score_spread":0.27198769573616816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410907582","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056022584,0.000083979394,0.9403122,0.00015650636,0.00003109686,0.00003606928,0.00002439101,0.000395831,0.002937377],"genre_scores_gemma":[0.7009972,0.000071792325,0.2966351,0.000098208526,0.000025874659,0.00007016773,0.00006380727,0.00014939677,0.0018884919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995223,0.00015779582,0.000020572163,0.00006508569,0.00017552903,0.00005868081],"domain_scores_gemma":[0.9990427,0.00046904047,0.00011886097,0.00017733064,0.00011706072,0.00007501231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013359084,0.00062560005,0.0004950435,0.00033450176,0.0003110888,0.00083313865,0.0007246973,0.000812796,0.0010848432],"category_scores_gemma":[0.0025886674,0.00033161926,0.00043168233,0.00020799275,0.0013571125,0.0008039794,0.0020095492,0.0011471463,0.00027287327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020487493,0.00013932804,0.0013112603,0.00014095398,0.00006967409,0.00013611194,0.00021991321,0.7680468,0.062394746,0.115302026,0.0017470578,0.050287247],"study_design_scores_gemma":[0.000006494697,0.000017957575,0.0000629503,0.0000031403697,0.0000015230652,0.000005889508,0.000007922887,0.9902265,0.0043632165,0.00500877,0.0002927487,0.0000028839759],"about_ca_topic_score_codex":0.0013232972,"about_ca_topic_score_gemma":0.0016969532,"teacher_disagreement_score":0.0013359084,"about_ca_system_score_codex":0.00036802242,"about_ca_system_score_gemma":0.00077761494,"threshold_uncertainty_score":0.007064998},"labels":[],"label_agreement":null}]}