ライフサイエンスコーパス: error

1 new stimulus-response mappings by trial-and-error.

2 ethod that fully corrects for this source of error.

3 is a time-consuming task and prone to human error.

4 r's spring constant were the main sources of error.

5 length, and spherical equivalent refractive error.

6 de is underway, the saccade appears to be in error.

7 dictions is comparable with the experimental error.

8 degeneration (AMD), glaucoma and refractive error.

9 tion protocols proceeds largely by trial and error.

10 mine the significance of the observed square error.

11 randomly assigned to intervention groups in error.

12 s and signal their deviation as a prediction error.

13 inuation of reinforcement through prediction errors.

14 justed or heteroscedasticity-robust standard errors.

15 rbed weighting of predictions and prediction errors.

16 to investigate patterns of commonly observed errors.

17 ncordance with replicative and translational errors.

18 rror and accounting for correlations between errors.

19 while retaining similar, and reliable type I errors.

20 g long reads contaminated by a high level of errors.

21 equent motor commands needed to reduce motor errors.

22 freque218 in a population are known without errors.

23 actually happens allows us to learn from our errors.

24 hich leads to ongoing chromosome segregation errors.

25 ich generates consensus but can also amplify errors.

26 correlate with the fitness cost of splicing errors.

27 repeat proteins likely reflecting alignment errors.

28 nts, but is limited by systematic and random errors.

29 substitutions and are more prone to splicing errors.

30 rse and unpredictable magnitude of the total errors.

31 x task of separating real polymorphisms from errors.

32 evoked by changes in kinematics or position errors.

33 used to compensate for upcoming reach extent errors.

34 AS11] over time [p = 0.03, beta +/- standard error = 0.7 +/- 0.3]; worse forgetting score on the Rey

35 AVLT) over time [p = 0.02, beta +/- standard error = -0.2 +/- 0.06]).

36 as excellent, with a slope of 0.97 (standard error, 0.04; P value [for difference from 1] =0.53) and

37 0.142), nonatypical MDD (B = 0.007 (standard error, 0.06); P = 0.911), and no history of depressive d

38 ] =0.53) and an intercept of 0.007 (standard error, 0.12; P value [for difference from 0] =0.95).

39 Atypical MDD (B = 0.41 (standard error, 0.15); P = 0.007) was a stronger predictor of inc

40 were dysthymic disorder (B = -0.31 (standard error, 0.21); P = 0.142), nonatypical MDD (B = 0.007 (st

41 romising (error: -0.09 +/- 0.59 mM, absolute error: 0.46 +/- 0.39 mM).

42 nce [K(+)] from blood samples was promising (error: -0.09 +/- 0.59 mM, absolute error: 0.46 +/- 0.39

43 s of vision loss were uncorrected refractive error (61.3%), cataract (13.2%), and age-related macular

44 were identified from 2493 opportunities for error (7.1% overall medication administration error rate

45 observed doses administered (or omitted) in error according to medication administration records, co

46 Weighing reduction in model error against increasing model complexity allowed for id

47 hanks to naturally finding the most probable error and accounting for correlations between errors.

48 To compare error and AE rates (1) gathered systematically with vs w

49 We take into account slope estimation error and examine phylogenetic, ecological and geographi

50 in low-resource settings could decrease user error and expand access to lifesaving outpatient antibio

51 ecent advances in the understanding of human error and individual and organizational performance.

52 y assessment instruments have both value and error and that this error should be considered in the an

53 In total, 179 errors and 113 AEs were identified from all sources.

54 ch repair gene MLH1 is driven by replication errors and accurately models the mutation profiles obser

55 the SS sensitivity to kinematics or position errors and are not due to differences in SS firing rates

56 ularly in view of biopsy-associated sampling errors and heterogeneous receptor expression in breast c

57 to and disclosing adverse events, including errors and near misses.

58 mizes false positives resulting from mapping errors and other technology specific artifacts including

59 osome amplification exhibit frequent mitotic errors and possess complex karyotypes, recapitulating a

60 can be tailored to correct common refractive errors and provide natural focus cues by dynamically upd

61 ve approach that corrects PCR and sequencing errors and removes PCR-mediated recombinant sequences (c

62 ewarding events is also driven by prediction errors and that, contrary to existing canon, dopamine tr

63 rent error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm

64 is based on a joint estimation of alignment errors, and the object, using an iterative refinement pr

65 These higher errors appear correlated with KC progression.

66 lumn packing, thus eliminating the trial and error approach commonly practiced today.

67 fficult and, typically, based on a trial-and-error approach.

68 Eyeballs having these refractive errors are known to exhibit abnormal eye shape at the an

69 combination with other well-known sources of error associated with PET/MRI examinations, lead to inco

70 nding affinity for 75% of cases and that the error associated with the predictions is comparable with

71 alternating dynamics only when the kinematic errors associated with each oppose one another.

72 ociates may achieve an acceptable refractive error at 7 years of age.

73 l quality assessment, i.e. assessment of the error at each residue position in a model.

74 etween the control (EFS, 35% +/- 3 [standard error] at 4 years) and clofarabine treatments (38% +/- 3

75 The large error bars for the R. inquisitor structures are intrinsi

76 field is to progress on less of a trial-and-error basis.

77 Moreover, numerical validations confirm an error below 0.02% for events at relatively large distanc

78 y-picked and unjustified stories emphasizing error, bias, the power of self-fulfilling prophecies, an

79 ced data contain subtle but complex types of errors, biases and uncertainties that impose several sta

80 elated fields and reaches three (1) Although errors, biases, and self-fulfilling prophecies in person

81 s characterized by a tripartite pattern: (1) Errors, biases, and self-fulfilling prophecies in person

82 xploited by cells to correct DNA replication errors both in growing cells and under nongrowing condit

83 ing these structural errors, diagnosed using error breeding, we develop a new forecast approach that

84 SNAP eliminates those errors by calculating the correct deflection sensitivity

85 se translations and then minimizes stitching errors by optimizing the translations within a (4r)(2) s

86 eading to a subjective sense of certainty or error (C2, consciousness in the second sense).

87 uity often requires time-consuming trial-and-error calculations using restrained molecular dynamics (

88 These errors can be avoided using a method for fluorescence qu

89 generate ordered networks, as it allows the error-checking that permits the network to crystallise,

90 aining, subjects were exposed to a series of error-clamp trials to measure the temporal characteristi

91 year, with Taylor series linearized standard errors clustered by state and classroom.

92 It has been suggested that social prediction errors-coding discrepancies between the predicted and ac

93 1.62*10(12) average copy number +/- standard error) compared to other tested viruses, with DWV second

94 ) to select the penalty parameter for type-1-error control, residual bootstrap (Lasso-RB), modified r

95 (whole-brain voxelwise analysis: familywise error corrected P=0.013) and longitudinal changes in ADA

96 icotinic acetylcholine receptors (familywise error-corrected P < .05).

97 braries from as little as 20 pg DNA with PCR error correcting capabilities, and capture target sequen

98 the probability distribution of errors in an error correcting code.

99 such low error values are the result of the error-correcting mechanism known as kinetic proofreading

100 After family-wise error correction across all traits (FWERacross), an incr

101 nd BLAT for sequence alignment and Fermi for error correction and sequence assembly.

102 ew forecast approach that combines dynamical error correction and statistical filtering techniques.

103 Our dissipative error correction scheme operates in a continuous manner

104 account the substantial overhead of quantum error correction, and the need to compile into discrete

105 However, Mps1's error correction-relevant substrates are unknown.

106 se relative to the characteristic split-belt error-correction mechanisms (i.e. muscle activity and ki

107 e tested (i) whether systematic localisation errors could reflect reliance on prior knowledge, as has

108 y processing; instead, the data suggest that error detection causes an attentional bottleneck, which

109 tor areas and is thought to be important for error detection, the dialogue between these two areas co

110 By counteracting these structural errors, diagnosed using error breeding, we develop a new

111 digitized filling flow, completely free from errors due to changes in viscosity.

112 frequent multistep saccades and directional errors during the antisaccade task than controls.

113 om forests that includes various options for error estimation techniques.

114 d framework can enable the quantification of error estimations and output variations in image segment

115 methods is prone to considerable systematic errors even in well-designed experimental setups.

116 e negative and 27 positive for mecA No major errors for cefoxitin were observed, but 19.5% very major

117 d-Altman analysis showed similar measurement errors for single-BH SSIR and non-BH SSIR when compared

118 polyubiquitin chains, previously involved in error-free damage tolerance.

119 n synthesis, polyubiquitination activates an error-free pathway, elusive in mammals, enabling damage

120 human DNA polymerase-iota (Poliota) promotes error-free replication across 1-MeA.

121 ucts, which gives insights how Rev1 achieves error-free replication.

122 trand DNA synthesis and subsequent bypass by error-free template switching.

123 79 oligos) without pre-purification, and the error-frequency was reduced from 14.25/kb to 0.53/kb.

124 -6)), whereas C-->G, U-->A, G-->C, and C-->A errors from purine-purine and pyrimidine-pyrimidine mism

125 red results fell within the Parkes consensus error grid zones.

126 ity of participants (65.1%) among refractive error group (REG) were above the age of 30 years, with a

127 The error has not been fixed in the paper.

128 that TSRI estimators with modified standard errors have correct type I error under the null.

129 Consistent with the "prediction error" hypothesis, activation was significantly higher a

130 blished version of this Article contained an error in Equation 1.

131 ace spectrometer can reduce the nonlinearity error in k-space from 14.86% to 0.47% (by approximately

132 ia risk factors or nonamblyogenic refractive error in most studies of test accuracy and were greater

133 outcomes and computes a negative prediction error in Pavlovian conditioning.

134 he LHb promotes a negative reward prediction error in Pavlovian conditioning.SIGNIFICANCE STATEMENT S

135 ogs have been posed as a potential source of error in somatostatin receptor imaging through interfere

136 riginal version of this Article contained an error in the abstract, referring to "multi-megawatt-per-

137 ubling dilution series, which means that any error in the reference method inherently represents at l

138 riginal version of this article contained an error in the spelling of the author Christian A.M. Wilso

139 y, we have corrected a previously identified error in the transmembrane region of the original cryo-e

140 fer from background noise, show a systematic error in which the particle sub-pixel positions are bias

141 nored in a simple Cox model, robust standard errors in a variance-correction model, random effect in

142 ently encode the probability distribution of errors in an error correcting code.

143 standard approach to eliminating confinement errors in bacterial cells is to analyze molecule displac

144 repair (MMR) pathway recognizes and repairs errors in base pairing and acts to maintain genome stabi

145 affected by the juice color, which generated errors in excess of 15%.

146 hydrophone method due to the absence of the errors in hydrophone spatial-averaging measurement and t

147 In these situations, we show how errors in positions can be corrected essentially complet

148 ation opposite dT, predicting frequent A-->G errors in RNA with rates of approximately 10(-4) The A--

149 late spline interpolation is used to correct errors in segmentation and check consistency of assigned

150 ucts containing splice site alleles revealed errors in splicing.

151 However, inborn errors in STAT4, which controls interleukin-12 (IL-12) r

152 Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing.

153 ved significantly in recent years, remaining errors in the Boltzmann weights are still on the order o

154 d cosine transform method can generate large errors in the calculation of saliency information becaus

155 We found errors in the data used to support the initial claim of

156 cases, they are not restricted to signaling errors in the prediction of value.

157 We show that errors in the UMI sequence are common and introduce netw

158 erver attempts to identify and to fix likely errors in user supplied 3D models of proteins via succes

159 ng the function of the aggression; trial-and-error; ingrained local custom (especially around instruc

160 report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasti

161 aerosol inhomogeneities introduce systematic error into the averages.

162 To prevent errors introduced by noise from multiplying and spreadin

163 analyses in which adjustment for measurement error is explored.

164 s and experimental results show the observed error is the result of electrostatic assumptions within

165 increases coordination of care and decreases errors, its effect on primary nonadherence is less certa

166 Segregation errors lead to an abnormal chromosome number (aneuploidy

167 LOQ (0.010mgmL(-1)), and more accurate with error less than 5% while results from the titrimetric me

168 model (average normalized root mean squared error </=11.3%) was then used to evaluate the product wa

169 implementation in three case studies with an error <1%.

170 The Goldmann-type tonometer error measured on live human eyes was 5.2 +/-1.6 mmHg lo

171 sociations using polynomial terms in spatial error models adjusted for total population and populatio

172 Increased neural error monitoring, as measured by the error-related negat

173 s, emotional regulation, and impulse control/error monitoring.

174 ry-type diplopia), 1 (4%) optical/refractive error (monocular diplopia), 2 (8%) mixed retinal misregi

175 G-->A, A-->U, C-->U, G-->U, U-->C, and U-->G errors mostly due to pyrimidine-purine mismatches were r

176 Mean prediction error (MPE) and root mean squared prediction error (RMSP

177 eye toward understanding why identification errors occur and what can be done to prevent them.

178 ites and to heteroionic soils (mean absolute error of 0.27 log unit).

179 cover map with a normalized root-mean-square error of 0.63.

180 ent agreement with experiment (mean unsigned error of 0.81 kcal/mol and Pearson correlation of 0.75).

181 ical and experimental datasets, we assign an error of 1.1-1.2 log unit for equilibrium constants of s

182 turned a more modest accuracy (mean unsigned error of 1.76 kcal/mol and Pearson correlation of 0.48);

183 tra-day repeatability with a mean percentage error of 18.7% and 32.8% for PLS and univariate calibrat

184 height + 18.3; R(2) = 0.51) with an average error of 3.3%.

185 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the re

186 f global NO2 variation, with a mean absolute error of 3.7 ppb.

187 pt studies of tissue phantoms yielded a mean error of 9.2% on hemoglobin concentration measurement, c

188 s a good fit with the data (root mean square error of approximation = 0.06; comparative fit index = 0

189 In PLS-R the Root Mean Square Error of Cross Validation (RMSECV) for parasite concentr

190 dominant STAT4 deficiency as a novel inborn error of IL-12-dependent IFN-gamma immunity associated w

191 hus, human MDA5 deficiency is a novel inborn error of innate and/or intrinsic immunity that causes im

192 ylalanine hydroxylase deficiency), an inborn error of metabolism, can be detected through newborn scr

193 ld type strain, we decrease the mean squared error of predicted central metabolic fluxes by approxima

194 rmance was evaluated by the root mean square error of prediction (RMSEP) and the correlation coeffici

195 activation pattern may reflect a prediction error of the brain, where rewards at unexpected times (1

196 xpressed as mean nmol/g protein +/- standard error of the mean, p = 0.040 by ANOVA).

197 eline with both krill oil (mean +/- standard error of the mean: -18.6+/-4.5 mOsmol/l; n = 18; P < 0.0

198 current that trace Langmuir isotherms within error of those seen in solution.

199 tolic, and pulse pressure bias and precision errors of -0.6 to 2.6 and 6.8 to 9.0 mmHg.

200 overy and characterization of several inborn errors of immune-related genes that underlie inherited h

201 rate quantification of biomarkers for inborn errors of metabolism (IEM) from dried blood spots (DBS)

202 isorders are among the most prevalent inborn errors of metabolism but largely lack treatments and hav

203 erapy for hematological malignancies, inborn errors of metabolism, and immunodeficiency disorders, ye

204 Inborn errors of OXPHOS function are termed primary mitochondri

205 onally illustrate that our approach achieves errors of roughly 5% in predicting the scattering proper

206 nterquartile range and the root-mean-squared error) of load estimates a modeling exercise showed that

207 ray-matter volume (F1,74 = 28.32; familywise error P threshold = 0.03), greater IC task-related blood

208 e representation of reinforcement prediction error (PE) (the difference between received and expected

209 lel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort

210 ery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now

211 Moreover, trial-and-error processing cannot guarantee fabrication feasibilit

212 is mediated by the suppression of prediction error processing through the prefrontal cortex (PFC).

213 omponent, was predicted by an ERP measure of error processing, the Pe component.

214 Differences in correction of errors produced during replication of the leading and th

215 reventing untimely tRNA and mRNA binding and error prone translation.

216 ts as a backup attempt to intercept the more error-prone alternative NHEJ repair pathway by recruitin

217 ngency of checkpoint signaling, resulting in error-prone chromosome segregation.

218 We link error-prone DNA polymerase activity to the generation of

219 solvent-exposed conformation, which enables error-prone DNA replication past the adduct.

220 It can replace expensive and error-prone manual parsing and standardization of scient

221 10 genes) in Escherichia coli using a highly error-prone microchip-synthesized oligo pool (479 oligos

222 ce in the absence of centrosomes, this is an error-prone process that opens up the fly to development

223 either endonuclease activity and subsequent error-prone repair have left a mutational footprint on t

224 Because apurinic sites are subject to error-prone repair, leading to substitution and short fr

225 bonucleotides are removed by NER followed by error-prone resynthesis with DnaE.

226 ted into the single-strand nick required for error-prone synthesis is an open question.

227 process is subjective, nonquantitative, and error-prone.

228 multiple sequencing platforms with different error properties; it minimizes false positives resulting

229 We propose the total error rate (TER), a novel performance measure for segmen

230 To control the overall type I error rate at 0.05, a hierarchical testing strategy was

231 ycle stages, we reach a sixfold reduction in error rate compared to a recent approach based on boosti

232 The transcription error rate estimated from mistakes in end product RNAs i

233 g long reads albeit with a relatively higher error rate in unprocessed data.

234 e describe an algorithm that solves the high error rate problem by combining long, high-error reads w

235 ized benchmarking, which reports a different error rate that is not sensitive to all errors, and cann

236 The medication administration error rate was calculated as the number of observed dose

237 rror (7.1% overall medication administration error rate).

238 are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), wher

239 data, and then computing BDA-optimal type 1 error rates and sample sizes for oncology RCTs.

240 However, Type-I error rates are controlled after applying the data adapt

241 ability to sequence single-cell genomes with error rates as low as 10(-8) and average 500-kb-long DNA

242 plying the optimal alpha approach results in error rates as low or lower than error rates obtained wh

243 re accurate Illumina sequencing reads, whose error rates average <1%.

244 ted when comparing medication administration error rates between original medication packaging (from

245 We establish small error rates in the identification of evoked spikes, with

246 results in error rates as low or lower than error rates obtained when using (i) no post-hoc adjustme

247 The average error rates of T7 RNAP (2 x 10(-6)), yeast mitochondrial

248 Herein, we report the error rates of three single-subunit RNAPs measured from

249 Error rates with family reporting (45.9 per 1000 patient

250 forms well as measured by type I and type II error rates.

251 h error rate problem by combining long, high-error reads with shorter but much more accurate Illumina

252 ted greater brain response 1) for prediction error regression within the caudate, ventral caudate/nuc

253 neural error monitoring, as measured by the error-related negativity (ERN), is a transdiagnostic neu

254 ive frontocentral evoked response similar to error-related negativity, which has in turn been implica

255 were used to investigate the time course of error-related processing while humans performed a diffic

256 ility modulated the expression of prediction error responses in anterior insula and insula-vmPFC conn

257 (2) > 0.72) with acceptable root mean square error RMSE.

258 etermination (R(2)) and the root mean square error (RMSE) from 3250 samples used for calibration and

259 error (MPE) and root mean squared prediction error (RMSPE) for daily predictions are 1.78 and 2.83 mu

260 ements by using regression, root-mean-square error, root-mean-square deviation, Lin concordance corre

261 in dopamine neurons signal reward prediction error (RPE), or actual minus expected reward.

262 nd depressive symptoms (r g = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; r

263 sion [SAC-C]), and balance (modified Balance Error Scoring System [mBESS] and tandem gait).

264 oefficient (r) = 0.789, standard estimate of error (SEE) = 24.470 cm(2), p < 0.001), Lin's correlatio

265 idal and retinal folds, hyperopic refractive error shifts, and nerve fiber layer infarcts.

266 ents have both value and error and that this error should be considered in the analysis and interpret

267 ible, and/or require a continuous, real-time error signal to guide learning.

268 Prediction-error signals consistent with formal models of "reinforc

269 sted that the superior colliculus (SC) sends error signals to drive saccade adaptation.

270 inimally affected the activity, fidelity and error specificity of Polzeta complexes.

271 network estimation and lower classification error than that achieved by other state-of-the-art metho

272 imitations of this study include measurement error that could lead to residual confounding; and the p

273 dissociate the subtypes of reward-prediction errors that function as the key computational signatures

274 tify and bioinformatically remove polymerase errors that otherwise make detection of these rare varia

275 hematopoietic stem cells, and few monogenic errors that specifically interrupt NK cell development h

276 ode novelty in addition to reward prediction error (the discrepancy between actual and predicted valu

277 ation, and doesn't reflect reward prediction error, timing, or value as single factors alone.

278 million), because of uncorrected refractive error to 8.0 million (2.5 million to 16.3 million), and

279 aqueous matrix solution allowed experimental error to be minimized to within 1% RSD.

280 s (OLS) regression using Newey-West standard errors to accommodate for serial autocorrelation, and ad

281 n records, compared to the opportunities for error (total number of observed doses plus omitted doses

282 modified standard errors have correct type I error under the null.

283 ped method for modeling cell decision making errors under normal and abnormal conditions, and in the

284 ory preconditioning, we show that prediction errors underlying stimulus-stimulus learning can be bloc

285 model that was adapted to test if prediction error valence influences learning.

286 It is widely believed that such low error values are the result of the error-correcting mech

287 ically significant positive predictor of the error variance for acute (R(2) = 0.20; P < 0.0001) and d

288 efoxitin were observed, but 19.5% very major errors (VMEs) were observed at 24 h of incubation, and 1

289 h the validation dataset, and mean predicted error was calculated for all regions using both WBN and

290 The square error was calculated to measure how well Y is predicted

291 I) and area manipulation to match a reported error, we are unable to replicate post-FISP production g

292 arious devices, despite which large standard errors were found for both intercepts and slope conversi

293 and seventy eight medication administration errors were identified from 2493 opportunities for error

294 Systematic errors were observed locally for key functional groups a

295 te valence-induced bias: negative prediction errors were preferentially taken into account, relative

296 g-Poisson regression with empirical standard errors were used to estimate the continuous and categori

297 e network-based methods to account for these errors when identifying PCR duplicates.

298 this finding to a positive reward prediction error, whereby the animal perceives they received a bett

299 ic kinase PLK1 drives chromosome segregation errors, with a specific focus on Gravin, a PLK1 scaffold

300 (method 5) led to the largest quantification errors (xSPECT, 32.3%; Flash3D, 46.7%).