wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We establish that under weak assumptions the estimator  concentrates in a 1 /root n neighborhood of the target with deviations controlled by the normal laws, and the estimator attains the semi-parametric efficiency bound in many cases. In particular, either the approximation to the regression function or the approximation to the Riesz representer can be "dense" as long as one of them is sufficiently "sparse". Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models\to  .
Revised:  We establish that under weak assumptions the estimator concentrates in a 1 /root n neighborhood of the target with deviations controlled by the Gaussian law, provided L/root(n)\to .
Edit intent: meaning-changed
Original:  Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models\to  .
Revised:  Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models\to 0; L is the operator norm of the functional, measuring the degree of its non-regularity, with L diverging for local functionals (or under weak identification of the global functionals) .
Edit intent: meaning-changed
Original: We provide novel adaptive inference methods, based on \ell_1 regularization, for regular ( semi-parametric ) and non-regular (nonparametric) linear functionals of the conditional expectation function.
Revised: We provide adaptive inference methods, based on \ell_1 regularization, for regular ( semi-parametric ) and non-regular (nonparametric) linear functionals of the conditional expectation function.
Edit intent: clarity
Original: We provide novel adaptive inference methods, based on \ell_1 regularization, for regular ( semi-parametric ) and non-regular (nonparametric) linear functionals of the conditional expectation function.
Revised: We provide novel adaptive inference methods, based on \ell_1 regularization, for regular ( semiparametric ) and non-regular (nonparametric) linear functionals of the conditional expectation function.
Edit intent: fluency
Original:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Revised:  Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Edit intent: clarity
Original:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Revised:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak " double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Edit intent: fluency
Original:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Revised:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness " : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Edit intent: fluency
Original:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Revised:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be "completely dense" as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Edit intent: fluency
Original:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently ``sparse'' . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Revised:  Under weak assumptions, the estimator of the functional concentrates in a L/\sqrt{n Our analysis yields weak `` double sparsity robustness '' : either the approximation to the regression or the approximation to the representer can be ``completely dense'' as long as the other is sufficiently "sparse" . Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters.
Edit intent: fluency
Original:  Our procedure is model-free and easy to implement, and provides useful visual information, which enables us to understand intuitively the properties of heterogeneity. We rst estimate the sample mean, autocovariances, and auto- correlations for each unit and then apply kernel smoothing to compute estimates of their density and cumulative distribution functions.
Revised:  We first estimate the sample mean, autocovariances, and auto- correlations for each unit and then apply kernel smoothing to compute estimates of their density and cumulative distribution functions.
Edit intent: coherence
Original:  The kernel estimators are consistent and asymptotically normal under double asymptotics, i.e., when both cross-sectional and time series sample sizes tend to in nity. However, as these exhibit biases given the incidental parameter problem and the nonlinearity of the kernel function, we propose jackknife methods to alleviate any bias .
Revised:  The kernel estimators are consistent and asymptotically normal under double asymptotics, i.e., when both cross-sectional sample size (N) and the time-series length (T). In particular, it makes the condition on N and T stronger and more complicated than those typically observed in the long-panel literature .
Edit intent: meaning-changed
Original: Although cell shape can reflect the mechanical and biochemical properties of the cell and its environment, quantification of 3D cell shapes within 3D tissues can be difficult, typically requiring digital reconstruction from a stack of 2D images.
Revised: Although cell shape can reflect the mechanical and biochemical properties of the cell and its environment, quantification of 3D cell shapes within 3D tissues remains difficult, typically requiring digital reconstruction from a stack of 2D images.
Edit intent: clarity
Original:  We investigate a simple alternative technique that can provide information about the 3D shapes of cells in a tissue from non-consecutive 2D slices. Our technique uses a 3D cell vertex model to construct a mapping between the 3D properties of interest and the distribution of shapes observed in  2D slices.
Revised:  We investigate a simple alternative technique that can provide information about the 3D shapes of cells in a tissue ; this technique connects the ensemble of 3D cell vertex model to construct a mapping between the 3D properties of interest and the distribution of shapes observed in 2D slices.
Edit intent: meaning-changed
Original:   We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Revised:  Using cell vertex model geometries, we find that the distribution of 2D shapes allows clear determination of the mean value of a 3D shape index. We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Edit intent: meaning-changed
Original:   We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Revised:  We analyze the errors that may arise in practice in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Edit intent: meaning-changed
Original:   We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Revised:  We analyze the errors that arise in the estimation of the mean 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Edit intent: fluency
Original:   We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Revised:  We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Edit intent: fluency
Original:   We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty in the mean 3D shape index below 2\\%.
Revised:  We analyze the errors that arise in the estimation of a 3D shape index from 2D imagery , and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty below 2\\%.
Edit intent: clarity
Original:  In this paper, we propose an algorithm based on algebraic methods to detect steady-states of stochastic reaction networks . The proposed method can be used to calculate necessary and sufficient parameters such that the stochastic reaction network has a prescribed number of steady-states .
Revised:  In this paper, we propose an algorithm based on algebraic methods to detect steady-states of stochastic reaction networks , in which the means and variances satisfy some given inequality constraints .
Edit intent: meaning-changed
Original:  In this zero-sum game, each box commits to a signal structure in order to maximize the chance that it is selected by the searcher at the completion of his search.
Revised:  In this zero-sum game, each box commits to a signal distribution as a function of quality before they learn their (random) quality; a firm's goal is to maximize the chance that it is selected by the searcher at the completion of his search.
Edit intent: meaning-changed
Original:  If there are no search frictions, then the problem reduces to the one examined in Hulko and Whitmeyer (2017). On the other hand, with search frictions,  if the expected value of the prize is sufficiently high, there is a symmetric equilibrium in pure strategies ;
Revised:  If there are no search frictions, there is a unique symmetric equilibrium in pure strategies; and for any finite number of firms, the signals are not fully informative. If there are search frictions, if the expected value of the prize is sufficiently high, there is a symmetric equilibrium in pure strategies ;
Edit intent: meaning-changed
Original: Consider a variation on the classic Weitzman search problem, in which  firms can choose how much information about their product to reveal to a consumer who decides to search them. In this zero-sum game, ex-ante identical firms commit to a signal distribution as a function of quality before they learn their (random) quality; a firm's goal is to maximize the chance that its product is the one selected by the searcher.
Revised: Consider a variation on the classic Weitzman search problem, in which firms can choose how much information about their product to reveal to a consumer .
Edit intent: clarity
Original:  If there are search frictions, then if the expected value of the prize is sufficiently high, there is a  symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Revised:  With search frictions, then if the expected value of the prize is sufficiently high, there is a symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Edit intent: coherence
Original:  If there are search frictions, then if the expected value of the prize is sufficiently high, there is a  symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Revised:  If there are search frictions, if the expected value of the prize is sufficiently high, there is a symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Edit intent: coherence
Original:  If there are search frictions, then if the expected value of the prize is sufficiently high, there is a  symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Revised:  If there are search frictions, then if the expected value of the prize is sufficiently high, there is a unique symmetric equilibrium in pure strategies, but if it is too low, there is no such pure strategy equilibrium .
Edit intent: meaning-changed
Original:  Remarkably, it is always beneficial to the searcher to have a slight search cost: a small search cost leads to the Perfect Competition level of information provision , but frictionless search leads to less informationrevelation in equilibrium.
Revised:  Remarkably, it is always beneficial to the searcher to have a slight search cost: a small search cost leads to the perfect competition level of information provision , but frictionless search leads to less informationrevelation in equilibrium.
Edit intent: fluency
Original:  Remarkably, it is always beneficial to the searcher to have a slight search cost: a small search cost leads to the Perfect Competition level of information provision , but frictionless search leads to less informationrevelation in equilibrium. This result is in sharp contrast to the famous Diamond paradox .
Revised:  Remarkably, it is always beneficial to the searcher to have a slight search cost: a small search cost leads to the Perfect Competition level of information provision : consumers gain when firms are forced to compete on information .
Edit intent: meaning-changed
Original:  With search frictions, if the expected value of the prize is sufficiently high, there is a unique symmetric equilibrium in which firms are fully informative.
Revised:  With search frictions, the information a visit will reveal depends in a systematic way on the ex-ante probability that a firm's product is high quality. When the expected quality of the product is sufficiently high, there is a unique symmetric equilibrium in which firms are fully informative.
Edit intent: meaning-changed
Original:  Remarkably , a small search cost leads to the perfect competition level of information provision: consumers gain when firms are forced to compete on information  .
Revised:  Remarkably , a small search cost leads to the perfect competition level of information provision: consumers gain when firms are forced to compete on information . Conversely, in the low and medium expected quality cases there are no pure strategy equilibria. Instead, firms mix over a continuum of levels of information: in the low expected quality case they provide full information with probability zero; and in the medium expected quality case they provide full information with positive probability. In both cases there are mixed strategy equilibria in which the firms' realized information structures are Blackwell comparable. Moreover, though recall is permitted, in each case there are equilibria in which the consumer never returns .
Edit intent: meaning-changed
Original:  If there are no search frictions, then there is a unique symmetric equilibrium in pure strategies, and the firms are not fully informative. With search frictions, the information a visit will reveal depends in a systematic way on the ex-ante probability that a firm's product is high quality.
Revised:  If there are no search frictions, then there is a unique symmetric equilibrium of this game, which, due to the countervailing incentives of attraction and persuasion, generates a payoff function for each firm that is linear in the information a visit will reveal depends in a systematic way on the ex-ante probability that a firm's product is high quality.
Edit intent: meaning-changed
Original:  With search frictions, the information a visit will reveal depends in a systematic way on the ex-ante probability that a firm's product is high quality. When the expected quality of the product is sufficiently high , there is a unique symmetric equilibrium in which firms are fully informative.
Revised:  With search frictions, the information a visit will reveal depends in a systematic way on the ex-ante probability that a firm's realized effective value. If the expected quality of the product is sufficiently high , there is a unique symmetric equilibrium in which firms are fully informative.
Edit intent: meaning-changed
Original:  When the expected quality of the product is sufficiently high , there is a unique symmetric equilibrium in which firms are fully informative. There, a small search cost leads to the perfect competition level of information provision--consumers gain when firms are forced to compete on information . Conversely, in the low and medium expected quality cases there are no pure strategy equilibria.
Revised:  When the expected quality of the product is sufficiently high (or competition is sufficiently fierce), this corresponds to full information--search frictions beget the first-best level of information provision--consumers gain when firms are forced to compete on information . Conversely, in the low and medium expected quality cases there are no pure strategy equilibria.
Edit intent: clarity
Original:  There, a small search cost leads to the perfect competition level of information provision--consumers gain when firms are forced to compete on information . Conversely, in the low and medium expected quality cases there are no pure strategy equilibria. Instead, firms mix over a continuum of levels of information : in the low expected quality case they provide full information with probability zero; and in the medium expected quality case they provide full information with positive probability. In both cases there are mixed strategy equilibria in which the firms' realized information structures are Blackwell comparable. Moreover, though recall is permitted, in each case there are equilibria in which the consumer never returns .
Revised:  There, a small search cost leads to the perfect competition level of information provision. If not, this corresponds to information dispersion--firms randomize over signals. If the attraction incentive is absent (due to hidden information or costless search), firms reveal less information and information dispersion does not arise .
Edit intent: meaning-changed
Original: We employ stochastic dynamic microsimulations to analyse and forecast the pension cost dependency ratio for England and Wales from 1991 to 2061, evaluating the impact of  state pension reforms initiated by the Labour and continued by the Conservative governments .
Revised: We employ stochastic dynamic microsimulations to analyse and forecast the pension cost dependency ratio for England and Wales from 1991 to 2061, evaluating the impact of the ongoing state pension reforms initiated by the Labour and continued by the Conservative governments .
Edit intent: meaning-changed
Original: We employ stochastic dynamic microsimulations to analyse and forecast the pension cost dependency ratio for England and Wales from 1991 to 2061, evaluating the impact of  state pension reforms initiated by the Labour and continued by the Conservative governments .
Revised: We employ stochastic dynamic microsimulations to analyse and forecast the pension cost dependency ratio for England and Wales from 1991 to 2061, evaluating the impact of state pension reforms and changes in international migration patterns under different Brexit scenarios .
Edit intent: meaning-changed
Original:  To a lesser degree, the future pension cost dependency ratio will depend also on the post-Brexit relations between the UK and the EU, with "soft" alignment on the free movement lowering the relative cost of the pension system compared to the "hard" one.
Revised:  To a lesser degree, the future pension cost dependency ratio will depend on the post-Brexit relations between the UK and the EU, with "soft" alignment on the free movement lowering the relative cost of the pension system compared to the "hard" one.
Edit intent: coherence
Original:  Further, assuming the local variance to be a piecewise linear function of strike and piecewise constant function of time this ODE is solved in closed form in terms of Bessel and hypergeometric functions.
Revised:  Further, assuming the local variance to be a piecewise linear function of strike and piecewise constant function of time this ODE is solved in closed form in terms of Confluent hypergeometric functions.
Edit intent: meaning-changed
Original:  Calibration of the model to market smiles does not require solving any optimization problem and, in contrast, can be done term-by-term by solving a system of non-linear algebraic equations for each maturity, which is ultra-fast .
Revised:  Calibration of the model to market smiles does not require solving any optimization problem and, in contrast, can be done term-by-term by solving a system of non-linear algebraic equations for each maturity, which is fast .
Edit intent: clarity