wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) and trying to adjust the time-independent parameters included in those models, we introduce dynamical parameters whose time-dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data.
Revised:  Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) to fit the data by adjusting the time--independent parameters included in those models, we introduce dynamical parameters whose time-dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data.
Edit intent: meaning-changed
Original:  Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) and trying to adjust the time-independent parameters included in those models, we introduce dynamical parameters whose time-dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data.
Revised:  Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) and trying to adjust the time-independent parameters included in those models, we introduce dynamical parameters whose time--dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data.
Edit intent: fluency
Original:  This phenomenological approach works extremely well to properly adjust the number of infected (and removed) individuals in time, for the countries we consider  .
Revised:  This phenomenological approach works extremely well to properly adjust the number of infected (and removed) individuals in time, for the countries we consider . Besides, it can handle the sub--epidemic events that some countries may experience. In this way, we obtain the evolution of the pandemic without using any a priori model based on differential equations .
Edit intent: meaning-changed
Original:  We started from a simple Susceptible, Infected, Recovered (SIR) model and we added the condition that, after a certain time, thebasic reproduction numberR0exponentially decays in time, as empirically suggestedby world data.
Revised:  We started from a simple Susceptible, Infected, Recovered (SIR) model and we added the condition that, after a certain time, the basic reproduction number R_0 exponentially decays in time, as empirically suggestedby world data.
Edit intent: clarity
Original:  We started from a simple Susceptible, Infected, Recovered (SIR) model and we added the condition that, after a certain time, thebasic reproduction numberR0exponentially decays in time, as empirically suggestedby world data.
Revised:  We started from a simple Susceptible, Infected, Recovered (SIR) model and we added the condition that, after a certain time, thebasic reproduction numberR0exponentially decays in time, as empirically suggested by world data.
Edit intent: fluency
Original:  Using this model, we were able to reproduce the real behavior of theepidemic within a confidence interval of 5 \%. Moreover, we illustrate possible futurescenarios, associated to different intervals ofR0. This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases. The real peak of the epidemic happened onthe 20th of April 2020, with 108.000 active cases. This result shows that the modelhas precise predictive power.
Revised:  Using this model, we were able to reproduce the real behavior of theepidemic within a confidence interval of 5 
Edit intent: coherence
Original:  We look at both continuous and discrete income distributions.
Revised:  Based on the observation that inequality functions (such as the Lorenz function), giving the measures of income or wealth against that of the population, to be generally nonlinear, we show that the fixed point (like Kolkata index k) of such a nonlinear function (or related, like the complementary Lorenz function) offer better measure of inequality than the average quantities (like Gini index). Indeed the Kolkata index can be viewed as a generalized Hirsch index for a normalized inequality function and gives the fraction k of the total wealth possessed by the rich (1-k) fraction of the population. We analyze the structures of the inequality indices for both continuous and discrete income distributions.
Edit intent: meaning-changed
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into ten themes, including " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Edit intent: fluency
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into 10 themes, such as " updates about confirmed cases," "COVID-19 related death," " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Edit intent: meaning-changed
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into 10 themes, such as " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Edit intent: fluency
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into 10 themes, such as " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ." Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Edit intent: fluency
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into 10 themes, such as " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatments and symptoms related messages as a prevalent topic on Twitter.
Edit intent: fluency
Original:  A total of salient 11 topics are identified and then categorized into 10 themes, such as "  cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as a prevalent topic on Twitter.
Revised:  A total of salient 11 topics are identified and then categorized into 10 themes, such as " cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive /Protective measures," "authorities," and "supply chain ". Results do not reveal treatment and /or symptoms related messages as prevalent topics on Twitter.
Edit intent: fluency
Original:  First, we conducted a time-frequency analysis with event-related spectral perturbation to represent the reliability of the brain signal while performing VP and VI . In addition, two types of decoding accuracies were obtained with the convolutional neural network to verify whether the brain signals can be distinguished from each class in the VP and whether they can be differentiated with VP and VI paradigms.
Revised:  First, we conducted a time-frequency analysis with event-related spectral perturbation . In addition, two types of decoding accuracies were obtained with the convolutional neural network to verify whether the brain signals can be distinguished from each class in the VP and whether they can be differentiated with VP and VI paradigms.
Edit intent: coherence
Original:  First, we conducted a time-frequency analysis with event-related spectral perturbation to represent the reliability of the brain signal while performing VP and VI . In addition, two types of decoding accuracies were obtained with the convolutional neural network to verify whether the brain signals can be distinguished from each class in the VP and whether they can be differentiated with VP and VI paradigms.
Revised:  First, we conducted a time-frequency analysis with event-related spectral perturbation to represent the reliability of the brain signal while performing VP and VI . In addition, two types of decoding accuracies were obtained with convolutional neural network to verify whether the brain signals can be distinguished from each class in the VP and whether they can be differentiated with VP and VI paradigms.
Edit intent: fluency
Original:  As a result, we obtained a high performance of 43.00\% (chance level is 16.67\%) in the 6-class classification (VP) of subject 1. The average performance was 32.56\% . Also, the binary classification performance which classifies two paradigms was 90.16\% .
Revised:  As a result, we obtained a high performance of 43.00\% (chance level is 16.67\%) in the 6-class classification performance in VP was 32.56\% . Also, the binary classification performance which classifies two paradigms was 90.16\% .
Edit intent: clarity
Original:  The average performance was 32.56\% . Also, the binary classification performance which classifies two paradigms was 90.16\% . These results indicate that the use of the proposed method is beneficial for the classification and prediction of the brain states from visual tasks (i.e. VP and VI) when developing comfortable BCI systems .
Revised:  The average performance was 32.56\% . Also, the binary classification performance which classifies two paradigms was 90.16\% .
Edit intent: coherence
Original: Background: The outbreak of Coronavirus disease 2019 (COVID-19) emerged in China at the end of 2019 and has spread worldwide within few weeks reaching a pandemic status. China and Italy, followed by other countries, have implemented strict control measures including complete lockdown. The effects of such measures and the optimal strategies to relax them are major Public Health concerns. Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks.
Revised: OBJECTIVES: to describe the first wave of the COVID-19 pandemic with a focus on undetected cases and to evaluate different post-lockdown scenarios. DESIGN: the study introduces a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks.
Edit intent: clarity
Original:  Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks.
Revised:  Method: We introduce a SEIR compartmental model , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks.
Edit intent: clarity
Original:  Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks.
Revised:  Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions , and the personal protective measures adopted as frequent hand washing or use of masks.
Edit intent: coherence
Original:  Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted as frequent hand washing or use of masks. Results: The model is experimentally validated with data of  Italian regions, European countries and US, obtaining fitting parameters in good agreement with previous literature.
Revised:  Method: We introduce a SEIR compartmental model describing the COVID-19 pandemic , taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions fitting Google COVID-19 Community Mobility Report data , and the personal protective measures adopted , such as wearing a mask and washing hands frequently. SETTING AND PARTICIPANTS: the model is experimentally validated with data of Italian regions, European countries and US, obtaining fitting parameters in good agreement with previous literature.
Edit intent: clarity
Original:  Results: The model is experimentally validated with data of  Italian regions, European countries and US, obtaining fitting parameters in good agreement with previous literature.
Revised:  Results: The model is experimentally validated with data of Italian regions, some European countries, and the US. MAIN OUTCOME MEASURES: the accuracy of the model results is measured through the mean absolute percentage error (MAPE) and Lewis criteria; fitting parameters are in good agreement with previous literature.
Edit intent: meaning-changed
Original:  The mean absolute percentage error analysis for forecasting accuracy judgement showed that our model was highly accurate in 12 regions (46\%), good in 7 (27\%) and reasonable in 7 (27\%). The estimation of the undetected cases allows to evaluate different post-lockdown scenarios which is crucial for public-health decision makers. Conclusions: The proposed model , calibrated and designed on measured or literature-based parameters, was successfully applied in all scenariosanalyzed and the estimation of the dynamic of the whole number of infectious individuals could help the planning of different strategies aimed at relaxing the lockdown measures .
Revised:  RESULTS: the epidemic curves for different countries and the dynamic of the whole number of infectious individuals could help the planning of different strategies aimed at relaxing the lockdown measures .
Edit intent: meaning-changed
Original:  Conclusions: The proposed model , calibrated and designed on measured or literature-based parameters, was successfully applied in all scenariosanalyzed and the estimation of the dynamic of the whole number of infectious individuals could help the planning of different strategies aimed at relaxing the lockdown measures .
Revised:  Conclusions: The proposed model , calibrated and designed on measured or literature-based parameters, was successfully applied in all scenariosanalyzed and the estimation of the amount of undetected and asymptomatic cases are estimated, which are likely to represent the main source of infections in the near future. The model is applied to the Hubei case study, which is the first place to relax mobility restrictions. Results show different possible scenarios. Mobility and the adoption of personal protective measures greatly influence the dynamics of the infection, determining either a huge and rapid secondary epidemic peak or a more delayed and manageable one. CONCLUSIONS: mathematical models can provide useful insights for healthcare decision makers to determine the best strategy in case of future outbreaks .
Edit intent: meaning-changed
Original: Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals  . Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2?
Revised: Network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals . Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2?
Edit intent: clarity
Original: Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals  . Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2?
Revised: Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2?
Edit intent: meaning-changed
Original: Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals  . Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2?
Revised: Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2?
Edit intent: clarity
Original:  We analyze population survey data showing that indeed the frequency of close-range contacts across individuals is characterized by a small fraction of people reporting very high frequencies of close-range contacts .
Revised:  We analyze population survey data showing that indeed the frequency of close-range contacts across individuals is characterized by a small fraction of people reporting very high frequencies . Strikingly, the average duration of contact is mostly invariant in the number of contacts, reinforcing the criticality of hubs .
Edit intent: meaning-changed
Original: Network scientists  proposed that infectious diseases  may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2  ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Revised: Network scientists have proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2 ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Edit intent: clarity
Original: Network scientists  proposed that infectious diseases  may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2  ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Revised: Network scientists proposed that infectious diseases involving person-to-person transmission may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2 ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Edit intent: clarity
Original: Network scientists  proposed that infectious diseases  may be effectively halted by targeting interventions at a minority of highly connected individuals , or hubs . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2  ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Revised: Network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals . Can this strategy be effective in combating a disease transmitted through physical proximity such as SARS-CoV-2 ? Effectiveness critically depends on high between-person variability in the number of close-range contacts.
Edit intent: clarity