ライフサイエンスコーパス: error

1 and hence their accurate quantification (<5% error).

2 ey assume individuals are identified without error.

3 rotein 1A1Z with as high as +/-4 Hz of added error.

4 and voxel repositioning are major sources of error.

5 e-one-out stability and thereby the expected error.

6 owever, they showed a high root mean squared error.

7 The publishers apologize for the error.

8 reward predictive cues as well as prediction error.

9 but humans cannot perform this task without error.

10 which are unavoidably subject to measurement error.

11 in the development of myopia and refractive error.

12 ciculation, it does not induce topographical errors.

13 xtrinsic correction systems that remove Pole errors.

14 elopers and users to reduce the risk of such errors.

15 ence of missing genotype data and genotyping errors.

16 ut is adjusted adaptively to minimize timing errors.

17 which results in increased Type I or Type II errors.

18 changes in gene expression, or more mitotic errors.

19 e data from DNA degraded with as much as 10% errors.

20 ied by an attenuation of positive prediction errors.

21 mporal and occipital lobes predicted reading errors.

22 rtefacts caused by sequencing and annotation errors.

23 ws to minimize the potential for performance errors.

24 subtle biases can cumulatively lead to large errors.

25 s employing the estimated means and standard errors.

26 ainty that some implementations will contain errors.

27 e published models with the root-mean-square errors 0.23-0.31 versus 0.23-0.97 log unit, and the pred

28 The normalized root mean square error (0.21 +/- 0.05 [mean SUV +/- standard deviation]),

29 or (0.35D versus 0.55D), and median absolute error (0.31D versus 0.51D) than the Haigis formula.

30 an error (0.45D versus 0.68D), mean absolute error (0.35D versus 0.55D), and median absolute error (0

31 smaller values in standard deviation of mean error (0.45D versus 0.68D), mean absolute error (0.35D v

32 as "almost perfect" (kappa = 0.922; standard error, 0.051).

33 encode a qubit protected against phase-flip errors(1,2).

34 phy after untreated nAMD were 9.6% (standard error, 1.2%), 31.4% (standard error, 2.2%), 43.1% (stand

35 tegravir clearance by 36% (relative standard error 13%) resulting in a 26% decrease in dolutegravir a

36 9.6% (standard error, 1.2%), 31.4% (standard error, 2.2%), 43.1% (standard error, 2.6%), and 61.5% (s

37 1.4% (standard error, 2.2%), 43.1% (standard error, 2.6%), and 61.5% (standard error, 4.3%) at 2, 5,

38 e; mean [SD] spherical equivalent refractive error, -2.39 [1.00] D).

39 24% more accurate (respective mean absolute errors: 3.11 versus 2.35 DOTs), resulting in 31-33% more

40 ecision (<5%) and accuracy (average relative error = 4.3%).

41 (standard error, 2.6%), and 61.5% (standard error, 4.3%) at 2, 5, 7, and 10 years, respectively.

42 tion interact during learning from trial and error across age groups.

43 ate phase after DMS infusions, and increased errors across phases after DLS infusions.

44 Specifically, prediction-error activation in the nucleus accumbens was similar ac

45 Refractive error alone accounted for 68.9% of childhood cases.

46 and addressing weaknesses identified in the error analysis.

47 od 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

48 n of height, weight, and BMI with refractive error and ocular biometric measures at age 15 years from

49 the combined influences of random diffusive error and systematic drift toward a set of stable states

50 Rather, errors and biases are primarily due to (a) systematic di

51 , frame-invariant, and robust to measurement errors and can be computed from unfiltered cell-velocity

52 Sequencing errors and convergent evolution did not account for thes

53 y-to-use web interface minimizing submission errors and eliminating the need for submitting sequencin

54 roscopic operations, frequent intraoperative errors and events, variation in surgeons' technical skil

55 , and the process is complicated by forecast errors and sparse wind measurements.

56 identifications were within +/-10 ppm (mass error) and with a P-Score <=1 x 10(-04).

57 using Pearson correlations, relative volume errors, and Bland-Altman analyses.

58 s characterized intraoperative distractions, errors, and events, and measured trainee involvement as

59 encoding choice outcomes, outcome prediction errors, and outcome history in their firing rates also c

60 ePCR outperforms PCR, reduces gross DNA errors, and provides a more uniform distribution of the

61 unction variants are enriched for annotation errors, and tend to be found at extremely low frequencie

62 rally recording sensory statistical learning errors, and used dynamic causal modeling to tap into the

63 cryo-EM, and that half-maps with independent errors are available in cryo-EM.

64 onditional mutagenesis to test whether these errors are due to the disruption of pioneer projections

65 Translational frameshift errors are often deleterious to the synthesis of functio

66 Higher-order many-body errors are small in both SCAN and self-interaction-corre

67 ue prediction that are history dependent and error based, providing plasticity essential for flexible

68 cated that precision weighting of prediction errors benefits learning in health and is impaired in ps

69 correction promises to eliminate sequencing errors, but the relative accuracy of error correction al

70 lso found beta-bursts were more common after errors, but their incidence was unrelated to response ti

71 easing the cross-validated root mean squared error by 1-42%, depending on the model.

72 nt satellite datasets reduced model ensemble error by better constraining unobservable processes and

73 al mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at rep

74 ep ResNets to perform residue-level ensemble error classifications at multiple predefined error thres

75 combines the predictions from the individual error classifiers for estimating the quality of a protei

76 Probabilistic models provide a low-error, compressed representation of single-cell data tha

77 ncoded, Decoded by Greedy Exhaustive Search) error-correcting code that repairs all three basic types

78 uencing errors, but the relative accuracy of error correction algorithms remains unknown.

79 r and how MCAK activity required for mitotic error correction is regulated by alpha-tubulin detyrosin

80 Computational error correction promises to eliminate sequencing errors

81 We combine an error correction strategy with a number of algorithmic i

82 lectron spins, which is required for quantum error correction, presents a challenge, and this goal re

83 short reads, which is referred to as hybrid error correction.

84 ther, in the context of motor learning where errors decrease across trials, people take into account

85 Because movement errors decreased exponentially across trials in both lea

86 d stimuli while passing forward unpredicted "errors." Different models have suggested distinct cortic

87 e show that, while removing self-interaction error does not alter the energetic ordering of the diffe

88 nteraction between motor preparation and the error-driven learning system may facilitate new probes i

89 on that extends beyond the classical view of error-driven supervised learning, as well as open questi

90 The DI is subject to substantial measurement errors due to cell offset from the flow centerline and v

91 Errors during meiotic resumption in oocytes can result i

92 nate mainly from DNA methylation maintenance errors during mitotic rather than during meiotic cell di

93 Resident physicians made more serious errors during the intervention schedules than during the

94 have so far largely been driven by trial and error efforts due to a critical lack of methods to probe

95 loidal nanoink onto a substrate with minimum error (error ratio < 2 x 10(-6)).

96 were most likely (strong negative prediction error), especially in subjects who obtained a better mod

97 cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD) perovskit

98 cations were predictive of distinct types of errors: failures-to-stop, failures-to-go, and incorrect

99 T), which begins at the epoch where training error first vanishes.

100 The constant error for the multi-to-single-joint condition (dominant:

101 The resulting prediction errors for both models were compared using the Wilcoxon

102 mization" (SRM), as it focuses on minimizing errors for cases that we know should have been predictab

103 that it is the commonest type of refractive error found amongst secondary school students.

104 te, indicating ATXN3's role in PNKP-mediated error-free C-NHEJ.

105 lf from the DNA following ETO washout, in an error-free manner.

106 ted performance indicates the possibility of error-free recovery of petabyte- and exabyte-scale data

107 Homologous recombination (HR) mediates the error-free repair of DNA double-strand breaks to maintai

108 sequencing protocol to eliminate sequencing errors from both simulated data and the raw reads.

109 outcome, when they encoded reward prediction errors graded by confidence, influencing subsequent choi

110 We discuss how these errors have affected downstream analyses and give recomm

111 king material engineering based on trial and error highly inefficient.

112 lar to those of other common DNA replication errors (i.e. ribonucleotide and mismatch insertions).

113 optical flow algorithm that helps us reduce error in blood perfusion estimate below 10% in different

114 The absolute error in counts (manual versus automated method) was cal

115 migrants, low response rate, and measurement error in estimating diet and activity from questionnaire

116 This implies a potential systematic error in millions of measurements over the past 30 years

117 the study may include potential measurement error in self-reported dietary intake, inability to clas

118 original paper [1], it was reported that an error in the processing of Fig.

119 The publisher apologizes for the error in versioning.

120 zes of bivariate outcomes and their standard errors in a 2-dimensional space.

121 insights into how the human brain represents errors in a task-dependent manner and guides subsequent

122 ties in human blastocysts arise from mitotic errors in around 70% of cases.

123 in prefrontal cortex with reward prediction errors in basal ganglia support exploration of latent ta

124 to different natural and nonnatural stimuli (errors in DNA replication, UV radiation, chemical agents

125 Severe developmental errors in E- embryos were characterized by improper nerv

126 applications in crystallography are that the errors in Fourier coefficients are largely in the phases

127 lates the assumption of Gaussian distributed errors in linear regression for eQTL detection, which re

128 ired for real-time performance, and with low errors in moment arms (below 5%) and lengths (below 0.4%

129 ng visual cues that could be used to correct errors in path integration in mouse medial entorhinal co

130 Notably, errors in precise forelimb placement emerged as a novel

131 els that model energy loss and thermal noise errors in realistic optical and microwave communication

132 actors might include reduction of systematic errors in sequencing data, incorporation of other data t

133 However, errors in sequencing have made any estimate of within-sa

134 lication of this Article the authors noticed errors in several figures.

135 ication of this Article, the Authors noticed errors in some of the Figures.

136 over, individuals with attenuated prediction errors in stable conditions were found to make greater i

137 t the inclusion of noise leads to systematic errors in the ability of these programs to measure expre

138 in the dorsal striatum: raclopride increased errors in the intermediate phase after DMS infusions, an

139 and the model identified and corrected three errors in the original individual identity assignments.

140 lexes are often extremely well-defined, with errors in the positions on the order of 10(-4)-10(-5) an

141 nput and do not have methods for identifying errors in the provided metadata, leading to the potentia

142 ty to record interviews, and possible subtle errors in translation.

143 y adverse events during surgery occur due to errors in visual perception and judgment leading to misi

144 imed to detect anomalies caused by technical errors in water-quality (turbidity and conductivity) dat

145 ncoded qubit with suppression of all logical errors, in quantitative agreement with a theoretical est

146 esigned; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and

147 ata and percentage of increased mean-squared error (%IncMSE) as measurement of feature importance.

148 ghborhood deregulation is quantified via the error incurred in predicting the expression of each gene

149 data identified two major sources of type I error inflation in this case-only test: linkage disequil

150 de that repairs all three basic types of DNA errors: insertions, deletions, and substitutions.

151 HEDGES also converts unresolved or compound errors into substitutions, restoring synchronization for

152 Medians of 20 errors (IQR 14-36) and 8 events (IQR 4-12) were identifi

153 Measurement error is common in epidemiology, but few studies use qua

154 e DNA, and upon recognition of a replication error it undergoes adenosine triphosphate-dependent conf

155 ysical thresholds closely (median fractional error <0.13).

156 The cross-validated mean absolute error (MAE) was evaluated for random forest-based predic

157 On the basis of the mean absolute prediction error (MAE), the formulas were ranked as follows: Kane k

158 ide a mechanism by which mnemonic prediction errors may drive memory updating-by biasing hippocampal

159 No additional major errors (MEs) or VMEs were found.

160 clude the following: they are prone to human error (microscopy) or expensive and time-consuming (poly

161 odel of human path integration, the Encoding-Error model.

162 In adolescence (15 y; n = 115), error monitoring event-related potentials were measured

163 The mean proportionate error (MPE) between iGFR-predicted and measured furosemi

164 Refractive error (myopia or hyperopia) was significantly associated

165 total students diagnosed to have refractive error (n = 92), myopia constituted 83/92 (90.2%) of the

166 The brain generates negative prediction error (NPE) signals to trigger extinction, a type of inh

167 ng accurate and reproducible with a standard error of +/-2.4%, was applied to a range of organophosph

168 on of 35.2 (14.2) years, and mean refractive error of -1.6 diopters.

169 equatorial East Indian Ocean with a standard error of 0.0060 kelvin.

170 n rates with a cross-validated mean absolute error of 0.13 mm/year and to reduce the required sample

171 with previous studies, with a mean unsigned error of 0.86 kcal/mol and root mean square error of 1.1

172 error of 0.86 kcal/mol and root mean square error of 1.11 kcal/mol, comparable with the accuracy of

173 od predicts the T(g) with a root-mean-square error of 13 degrees C for conjugated polymers with alkyl

174 well with average relative root mean square error of 26%, although uncertainty in model prediction w

175 elated with confounder variables reduces the error of inference by 30-35%, and that selection of cell

176 Glutaric aciduria type 1 (GA1) is an inborn error of lysine degradation characterized by a specific

177 on was greater at 38.5 +/- 1.7 mum (standard error of mean) than the temporal half at 4.1 +/- 2.1 mum

178 We report an inborn error of metabolism caused by TKFC deficiency in two unr

179 of determination (R(2)) and root mean square error of prediction (RMSEP).

180 ) hospitalised for at least 7 days, the mean error of Prediction of Hospital Discharge Date at day 7

181 ver 1000 DeltaG degrees values with standard error of roughly 0.05 kcal/mol.

182 quantification bias (defined as the standard error of the mean values) was conducted by comparing mea

183 =3, >=4, >=5, and >=6 months, mean (standard error of the mean) additional time treatment free was 1.

184 Median absolute error of TimeSignature was higher in individual critical

185 microcystin-LR equivalents can introduce an error of up to 6-fold and recommend a class-equivalent a

186 oproduct ratios were determined with maximum errors of 3%.

187 It is unknown whether these natural errors of face detection originate from a rapid process

188 osis of children and adolescents with inborn errors of immunity (IEIs).

189 ler cell deficiency (NKD) arises from inborn errors of immunity that lead to impaired NK cell develop

190 flammatory disease can result from monogenic errors of immunity.

191 hies) (30% of the genetic diagnoses); inborn errors of metabolism and musculoskeletal disorders (11%

192 Inborn errors of metabolism are genetic conditions that can dis

193 specifically directed toward various inborn errors of metabolism which may be helpful for answering

194 other primary immune deficiencies and inborn errors of metabolism.

195 reat promise as a diagnostic tool for inborn errors of metabolisms (IEMs) in the near future.

196 is an emerging phenotype accompanying inborn errors of type I interferon immunity.

197 Knowledge gaps (number of errors on 7 facts on COVID-19 symptoms and prevention) a

198 d method is found to have 10% lower tracking error over CMAC participants.

199 impact of dropouts or isoform quantification errors, potentially confounding the results of these ana

200 With an 80% statistical power and a type I error probability of 0.1, 48 patients were to be accrued

201 This trial-and-error process often results in cysteine-free proteins wi

202 , where spindle bipolarization is reportedly error prone, exhibit no detectable kinetochore enrichmen

203 exposure also results in the recruitment of error-prone DNA polymerases to the replication fork.

204 tic hypermutation (SHM) targeting, including error-prone DNA repair activities that are crucial to Ab

205 Additionally, due to the error-prone nature of viral RNA synthesis in an individu

206 locus, followed by repair through either the error-prone non-homologous end joining or the homology d

207 Error-prone PCR mutagenesis reinforced the importance of

208 nal replication forks lead to recruitment of error-prone polymerases.

209 res) faced the challenge of translating long error-prone reads from the nucleotide alphabet into the

210 d cytidine deaminase-induced DNA lesions and error-prone repair that underlie SHM are known to exhibi

211 The error-prone third-generation sequencing (TGS) long reads

212 studies either reduce available data or are error-prone, and thus, scalable methods that do not disc

213 ne them by hand, which is time-consuming and error-prone.

214 These errors propagate to the assembly and affect the accuracy

215 vided metadata, leading to the potential for error propagation.

216 ome a practical way to encode and manipulate error-protected quantum information.

217 d NHP ON datasets as judged by mean absolute error, R(2) values when regressing automated vs. manual

218 ALs averaged 26.3 +/- 0.3 mm (standard error [range 21.5-33.4 mm]).

219 spectrophotometry method and showed relative error ranging from 5 to 19%, and less than 9% when compa

220 Satisfactory recoveries and relative errors ranging from 97 to 99.3% and -4.0 to 2.4% were ob

221 ons (FDR 5%), six of which reach family-wise error rate (FWER) significance (p < 1.25E-06).

222 ial racial disparities, with an average word error rate (WER) of 0.35 for black speakers compared wit

223 he network describing protein synthesis, the error rate and the energy expenditure per peptide bond i

224 titution raised the organelle DNA polymerase error rate by 140-fold relative to the wild type enzyme.

225 fewer background regions, which reduced the error rate by 7%.

226 PLS-DA revealed models with smallest error rate for controls in bacterial component and inact

227 detect nucleotide substitution variants have error rates (about 10-3) that limit sensitive detection.

228 Average word error rates across a held-out repeat set are as low as 3

229 ping with supervised learning to achieve bit error rates as low as 0.11% for single reads, without li

230 large-sample data (N > 400,000) with type I error rates well controlled.

231 promoter architectures on decision times and error rates, present concrete examples that rapidly read

232 dataset by multiple researchers can inflate error rates.

233 losely related populations or with increased error rates.

234 der/decoder to account for the corresponding error rates.

235 transcribes certain genomic loci with higher errors rates.

236 nanoink onto a substrate with minimum error (error ratio < 2 x 10(-6)).

237 Cases of uncorrected refractive error remained the major cause for presenting visual imp

238 n safety emphasis and the fear of medication error reporting among Chinese nurses.

239 uthority, and the Nurses' Fear of Medication Error Reporting.

240 We measured prediction error responses to sound sequences with electroencephalo

241 wavelength, this setup avoids all sources of errors resulting from chromatic aberrations and detector

242 It had lower root mean square prediction error (RMSPE) than when using no tool (leaving sequencin

243 s include chromatin tracing, RNA multiplexed error-robust FISH (MERFISH), multiplexed imaging of nucl

244 LT-FH was 63% (standard error (s.e.) 6%) more powerful than GWAS and 36% (s.e. 4

245 t (HSCT; time to completion (part B-part A); error score in part B) as well as a 3D MRI.

246 olic HBP were associated with 5.07 (standard error [SE]: 1.48) and 3.92 (SE: 2.14) g/m(2) higher LVMI

247 uces its learning rate by virtue of lowering error sensitivity when faced with uncertainty.

248 Thinking the e-mail was a system error, she almost didn't learn that her genetic test res

249 This error signal is accompanied by alpha coherence between t

250 e reward learning (P = 0.001) and prediction error signalling (P = 0.004) were both associated with s

251 eward learning and reward-related prediction error signalling improved most.

252 eward and concomitantly corrupted prediction error signalling.

253 Whereas local reward prediction error signals are early and phasic in the PH tail, globa

254 ity paused, reflecting positive and negative error signals of a reward prediction.

255 ivity to generate sensory cue and prediction error signals that are essential for reward-based learni

256 g, and denoising level did not influence VNC(error) significantly, phantom size, iodine content and b

257 eters optimised to minimise cross validation error, ten methods of automated variable selection produ

258 new method is more powerful with less Type I error than the other two methods.

259 Am signatures exerted a lower classification error than the PBMC-based DNAm markers (p-value = 0.0002

260 faster (DOME and DVSS groups) and with fewer errors than controls (DOME group; P < 0.01).

261 it makes orders of magnitude fewer decoding errors than pure selectivity even when both forms of sel

262 in vitro experiments by incorporating model error that shifts the TGFbeta doses associated with the

263 ly interpreted as reflecting the replication errors that accrue during spermatogenesis.

264 are to fulfill their potential, the diverse errors that affect them must be understood and suppresse

265 with progressive accumulation of epigenetic errors that eventually lead to aberrant gene regulation,

266 DNA mismatch repair (MMR) corrects errors that occur during DNA replication.

267 we argue that coarse-grained data introduce errors that, in biological studies, are too often ignore

268 lue (SUV) of the normalized root mean square error, the peak signal-to-noise ratio, and the structura

269 ts moving direction to develop, by trial-and-error, the same motor routine whose execution resulted i

270 An extension of the prediction error theory of dopamine, imported from artificial intel

271 error classifications at multiple predefined error thresholds, and then combines the predictions from

272 f the contribution of chromosome segregation errors to the development of aneuploidy.

273 We then scaled the impact of these small errors to whole plant carbon balance and found that the

274 uated to a loss of 8.2 +/- 4.2 (one standard error) tonnes of carbon per hectare per year from the br

275 information in both subspaces is reduced in error trials.

276 versus automated method) was calculated and error types were categorized as false positives or negat

277 than when using no tool (leaving sequencing errors uncorrected).

278 l-free phasic dopaminergic reward-prediction errors underlie learning, which renders stimuli 'wanted'

279 proving its accuracy by correcting inference errors using pedigree structure.

280 ving a formula that links the TBR estimation error variance with the CGM recording length.

281 Poisson regression with robust error variance, clustered by site adjusting for calendar

282 ng publication of the original paper [1], an error was reported in the processing of Fig. 2.

283 Specifically, mean accuracy (prediction error) was 12.2% versus 78% and mean precision (width of

284 The highest accuracy and lowest error were observed with cystatin C-based chronic kidney

285 of exploration, exploitation and prediction error were unaffected.

286 al end-systolic circumferential Green strain errors were -0.001 +/- 0.025, -0.001 +/- 0.021, and 0.00

287 The corresponding angular errors were 0.94 +/- 0.83 degrees and 0.87 +/- 0.82 degr

288 ifferent motion scenarios compared to 20-30% error when using current approaches.

289 tions displayed high biases and unacceptable errors when compared with measured glomerular filtration

290 ampling by biopsy may be limited by sampling error, whereas non-invasive imaging can evaluate the ent

291 eak between 30,425 and 29,772 cal BP (2sigma error) which matches more depleted delta(18)O values in

292 outgroup learning signals (action prediction errors), which formally captured deficits in outgroup le

293 fast quantum control and robustness against errors, which is intrinsic to stabilized macroscopic sta

294 We model residual errors with a heavy-tailed Student's t-distribution to e

295 nd, Baltimore, found evidence that there are errors with the presentation of the standard deviations

296 ror within 1.18 mmHg) and WSS (mean absolute error within 0.99 Pa) for patients with this disease.

297 to accurately predict DeltaP (mean absolute error within 1.18 mmHg) and WSS (mean absolute error wit

298 , respectively, showed refractive prediction errors within +/-0.5 diopter (D); in eyes with toric IOL

299 ments regarding the estimation of prediction errors would derive in the calculation of other analytic

300 The majority of detected errors would result in amino-acid changes, if translated