wanyu/IteraTeR_full_sent huggingface dataset:
Original:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Revised:  These drops are much larger and faster than those previously reported and surprisingly do not have strong correlations to other model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Edit intent: clarity
Original:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Revised:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as contact rate) or other standard state/national metrics such as the population density, GDP, and median age.
Edit intent: clarity
Original:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Revised:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as population density, GDP, and median age.
Edit intent: fluency
Original:  Plausible causes for this drop are discussed , such as improvements in treatments , face mask wearing, a new virus strain, and age demographics of infected patients, but none alone support such large decreases .
Revised:  Plausible causes for this drop are discussed , such as improvements in treatments , face mask wearing, a new virus strain, and age demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Edit intent: meaning-changed
Original:  The power of the proposed approach is demonstrated through two experiments on a planar biped AMBER-3M: the first with rigid point feet , and the second with induced model uncertainty through the addition of springs where the added compliance was not accounted for in the gait generation or in the controller.
Revised:  The power of the proposed approach is demonstrated through two experiments on a planar biped AMBER-3M: the first with rigid point-feet , and the second with induced model uncertainty through the addition of springs where the added compliance was not accounted for in the gait generation or in the controller.
Edit intent: fluency
Original:  The results show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Revised:  The calculations of this newly tested model show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Edit intent: meaning-changed
Original:  The results show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Revised:  The results show that the value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Edit intent: clarity
Original:  The results show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Revised:  The results show that the calculated value of the coefficient of relative risk aversion is 1.033526 by assuming the value of the subjective time discount factor as 0.99. Since these values are compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Edit intent: meaning-changed
Original:  The results show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the empirical studies and as investors who invest in risk-free asset place disutility on the not sure wealth value, investors who invest in equity place utility on the not sure wealth value .
Revised:  The results show that the calculated value of the coefficient of relative risk aversion is 2.201455 which is compatible with the existing empirical studies, they confirm the validity of the newly derived model that provides a solution to the equity premium puzzle .
Edit intent: meaning-changed
Original: In this paper, the solution of the equity premium puzzle was given. First, the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool  was developed to study the risk behavior of investors .
Revised: In this paper, the solution of the equity premium puzzle . Questioning the validity of the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool was developed to study the risk behavior of investors .
Edit intent: clarity
Original:  First, the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool  was developed to study the risk behavior of investors .
Revised:  First, the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool , that is, the sufficiency factor of the model was developed to study the risk behavior of investors .
Edit intent: meaning-changed
Original:  First, the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool  was developed to study the risk behavior of investors . This new tool in the new formulated model was tested for the equity premium puzzle for a solution .
Revised:  First, the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors was questioned, and then a new tool was developed to study the risk behavior of investors .
Edit intent: coherence
Original: We consider discrete linear Chebyshev approximation problems , where the approximation criterion to minimize by fitting the unknown parameters of a linear function takes the form of the least maximum absolute deviation of errors. Approximation problems of this kind find application in the solution of overdetermined systems of linear equations that appear in many practical contexts.
Revised: We consider discrete linear Chebyshev approximation problems , where the approximation criterion to minimize by fitting the unknown parameters of a linear function takes the form of the least maximum absolute deviation of approximation errors. Such problems find wide application in the solution of overdetermined systems of linear equations that appear in many practical contexts.
Edit intent: clarity
Original: We reconsider a linear finite element method on a Bakhvalov-type mesh for a singularly perturbed problem with two parameters , which has been discussed in Brdar and Zarin (J. Comput.
Revised: In this paper, the linear finite element method on a Bakhvalov-type mesh for a singularly perturbed problem with two parameters , which has been discussed in Brdar and Zarin (J. Comput.
Edit intent: clarity
Original: We reconsider a linear finite element method on a Bakhvalov-type mesh for a singularly perturbed problem with two parameters , which has been discussed in Brdar and Zarin (J. Comput.
Revised: We reconsider a linear finite element method on a Bakhvalov-type mesh is applied to a singularly perturbed problem with two parameters , which has been discussed in Brdar and Zarin (J. Comput.
Edit intent: meaning-changed
Original: We reconsider a linear finite element method on a Bakhvalov-type mesh for a singularly perturbed problem with two parameters , which has been discussed in Brdar and Zarin (J. Comput. Appl. Math., 292 (2016), pp. 307--319). A novel interpolant is introduced for convergence analysis.
Revised: We reconsider a linear finite element method on a Bakhvalov-type mesh for a singularly perturbed problem with two parameters . The solution of the problem exists two exponential boundary layers. A new interpolation, which is simple in construction and analysis, is introduced for convergence analysis.
Edit intent: meaning-changed
Original:  From this interpolation, error analysis with Lagrange interpolation on the Bakhvalov-type mesh becomes feasible. As a result, we not only prove an optimal convergence between the true solution and the numerical solution, but also get a supercloseness result between the Lagrange interpolant and the numerical solution.
Revised:  From this interpolation, error analysis with Lagrange interpolation on the Bakhvalov-type mesh itself and the weaker exponential layer and obtain an interesting result. Finally, we prove a supercloseness result between the Lagrange interpolant and the numerical solution.
Edit intent: meaning-changed
Original:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Revised:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Edit intent: clarity
Original:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Revised:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Edit intent: clarity
Original:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Revised:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration library for MRA is still lacking.
Edit intent: clarity
Original:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is still lacking.
Revised:  This explains why a 2D classification approach based on multi-reference alignment (MRA) is not as popular as the Bayesian-based approach despite that the former has advantage in differentiating subtle structural variations under low signal-to-noise ratio (SNR) . This is perhaps because that MRA is a time-consuming process and a modular GPU-acceleration package for MRA is lacking.
Edit intent: clarity
Original:  OSM2KG significantly outperforms both na%DIFDELCMD < {\i}%%% ve baselines and state-of-the-art link discovery approaches and achieves up to 22.45 percent points increase in F1 score  compared to the best performing baselines.
Revised:  OSM2KG %DIFDELCMD < {\i}%%% ve baselines and state-of-the-art link discovery approaches and achieves up to 22.45 percent points increase in F1 score compared to the best performing baselines.
Edit intent: clarity
Original:  OSM2KG significantly outperforms both na%DIFDELCMD < {\i}%%% ve baselines and state-of-the-art link discovery approaches and achieves up to 22.45 percent points increase in F1 score  compared to the best performing baselines.
Revised:  OSM2KG significantly outperforms both na%DIFDELCMD < {\i}%%% achieves an F1 score of 92.05\% on Wikidata and of 94.17\% on DBpedia on average, which corresponds to a 21.82 percentage points increase in F1 score compared to the best performing baselines.
Edit intent: meaning-changed
Original:  OSM2KG significantly outperforms both na%DIFDELCMD < {\i}%%% ve baselines and state-of-the-art link discovery approaches and achieves up to 22.45 percent points increase in F1 score  compared to the best performing baselines.
Revised:  OSM2KG significantly outperforms both na%DIFDELCMD < {\i}%%% ve baselines and state-of-the-art link discovery approaches and achieves up to 22.45 percent points increase in F1 score on Wikidata compared to the best performing baselines.
Edit intent: meaning-changed
Original:  We evaluated the influence of tree species associated with two different mycorhizal types, ectomycorrhiza (EcM) and arbuscular mycorrhiza (AM), on growth, biomass and metabolic activity of soil fungal and bacterial communities using common garden tree species experimens throughout Denmark.
Revised:  We evaluated the influence of tree species associated with two different mycorrhizal types, ectomycorrhiza (EcM) and arbuscular mycorrhiza (AM), on growth, biomass and metabolic activity of soil fungal and bacterial communities using common garden tree species experimens throughout Denmark.
Edit intent: fluency
Original:  We evaluated the influence of tree species associated with two different mycorhizal types, ectomycorrhiza (EcM) and arbuscular mycorrhiza (AM), on growth, biomass and metabolic activity of soil fungal and bacterial communities using common garden tree species experimens throughout Denmark.
Revised:  We evaluated the influence of tree species associated with two different mycorhizal types, ectomycorrhiza (EcM) and arbuscular mycorrhiza (AM), on growth, biomass and metabolic activity of soil fungal and bacterial communities using common garden tree species experiments throughout Denmark.
Edit intent: fluency
Original:  The results indicated that microbial community composition and functioning differed between groups of tree species with distinct litter qualities that mediate soil C/N ratio and soil pH . The grouping of tree species partly coincided with their mycorrhizal association since lime was more similar to AM tree species.
Revised:  The results indicated that microbial community composition and functioning differed between groups of tree species with distinct litter qualities that mediate soil C/N ratio and soil pH differences. The mycorrhizal association only partly explained litter quality and soil microbial species differences since lime was more similar to AM tree species.
Edit intent: clarity
Original: A bipartite graph consists of two disjoint vertex sets, where vertices of one set can only be joined with an edge to vertices in the opposite set. Hall's theorem gives a necessary and sufficient condition for a bipartite graph to have a saturating matching , meaning every vertex in one set is matchedto some vertex in the other in a one-to-one correspondence.
Revised: I relate bipartite graph matchings to stable matchings. I prove a necessary and sufficient condition for a bipartite graph to have a saturating matching , meaning every vertex in one set is matchedto some vertex in the other in a one-to-one correspondence.
Edit intent: meaning-changed
Original:  Hall's theorem gives a necessary and sufficient condition for a bipartite graph to have a saturating matching , meaning every vertex in one set is matchedto some vertex in the other in a one-to-one correspondence.
Revised:  Hall's theorem gives a necessary and sufficient condition for the existence of a saturating stable matching, where every agent on one side is matched , meaning every vertex in one set is matchedto some vertex in the other in a one-to-one correspondence.
Edit intent: meaning-changed
Original:  Hall's theorem gives a necessary and sufficient condition for a bipartite graph to have a saturating matching , meaning every vertex in one set is matchedto some vertex in the other in a one-to-one correspondence. When we imagine vertices as agents and let them have preferences over other vertices, we have the classic stable marriage problem introduced by Gale and Shapley, who showed that one can always find a matching that is stable with respect to agent's preferences. These two results often clash: saturating matchings are not always stable, and stable matchings are not always saturating. I prove a simple necessary and sufficient condition for every stable matching being saturating for one side. I show that this result subsumes and generalizes some previous theorems in the matching literature. I find a necessary and sufficient condition for stable matchingsbeing saturating on both sides , also known as perfect matchings.
Revised:  Hall's theorem gives a necessary and sufficient condition for a bipartite graph to have a saturating matching , for all possible preferences. I extend my analysis to perfect stable matchings, where every agent on both sides , also known as perfect matchings.
Edit intent: meaning-changed
Original:  Machine learningtechniques , combined with sample-splitting, extract nonlinear variation in the instrument that may dramatically improve estimation precision and robustness by boosting instrument strength.
Revised:  Machine learningtechniques , combined with sample-splitting, to predict the treatment variable from the instrument and any exogenous covariates, and then use this predicted treatment and the covariates as technical instruments to recover the coefficients in the second-stage. This allows the researcher to extract non-linear co-variation between the treatment and instrument that may dramatically improve estimation precision and robustness by boosting instrument strength.
Edit intent: meaning-changed
Original:  The analysis is straightforward in the absence of covariates. The presence of linearly included exogenous covariatescomplicates identification, as the researcher would like to prevent nonlinearities in the covariates from providing the identifying variation. Our procedure can be effectively adapted to account for this complication, based on an argument by Chamberlain ( 1992).
Revised:  Importantly, we constrain the machine-learned predictions to be linear in the exogenous covariates, thus avoiding spurious identification arising from non-linear relationships between the treatment and the covariates rather than from the instrument itself. We show that this approach delivers consistent and asymptotically normal estimates under weak conditions and that it may be adapted to be semiparametrically efficient (Chamberlain, 1992).
Edit intent: clarity
Original:  Importantly, we constrain the machine-learned predictions to be linear in the exogenous covariates, thus avoiding spurious identification arising from non-linear relationships between the treatment and the covariates rather than from the instrument itself .
Revised:  Importantly, we constrain the machine-learned predictions to be linear in the exogenous covariates, thus avoiding spurious identification arising from non-linear relationships between the treatment and the covariates .
Edit intent: clarity
Original:  Results show that the EARDict model achieves new state-of-the-art performances on benchmark knowledge graph completion tasks, including a Hits@10 score of 80.38 percent on WN18RR.
Revised:  Results show that our EARDict model significantly outperforms all the benchmark models on two large datasets of knowledge graph completion tasks, including a Hits@10 score of 80.38 percent on WN18RR.
Edit intent: clarity
Original:  Results show that the EARDict model achieves new state-of-the-art performances on benchmark knowledge graph completion tasks, including a Hits@10 score of 80.38 percent on WN18RR.
Revised:  Results show that the EARDict model achieves new state-of-the-art performances on benchmark knowledge graph completion , including achieving a Hits@10 score of 80.38 percent on WN18RR.
Edit intent: clarity
Original:  Results show that the EARDict model achieves new state-of-the-art performances on benchmark knowledge graph completion tasks, including a Hits@10 score of 80.38 percent on WN18RR.
Revised:  Results show that the EARDict model achieves new state-of-the-art performances on benchmark knowledge graph completion tasks, including a Hits@10 score of 96.6 percent on WN18RR.
Edit intent: meaning-changed
Original:  Results show that our EARDict model significantly outperforms all the benchmark models on two large datasets of knowledge graph completion , including achieving a Hits@10 score of 96.6 percent on WN18RR.
Revised:  Results show that our EARDict model significantly outperforms all the benchmark models on three large datasets of knowledge graph completion , including achieving a Hits@10 score of 96.6 percent on WN18RR.
Edit intent: meaning-changed
Original:  Results show that our EARDict model significantly outperforms all the benchmark models on two large datasets of knowledge graph completion , including achieving a Hits@10 score of 96.6 percent on WN18RR.
Revised:  Results show that our EARDict model significantly outperforms all the benchmark models on two large datasets of knowledge graph completion . Especially, our model achieves a Hits@10 score of 96.6 percent on WN18RR.
Edit intent: clarity
Original:   When the noise is large or small, our numerical findings show that the COVID-19 vanishes from the people if \xi <1;
Revised:  The effects of these noises on the dynamics of the model are studied. The numerical experiments show that the random perturbation introduced in the stochastic model suppresses disease outbreaks as compared to its deterministic counterpart. In other words, the impact of the noises on the extinction and persistence is high. When the noise is large or small, our numerical findings show that the COVID-19 vanishes from the people if \xi <1;
Edit intent: meaning-changed