wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The first result is a polynomial normal form representation for discrete functionsthat provides a partition of the inputs of the function into canalizing and non-canalizing variables and, within the canalizing ones, we categorize the input variables into layers of canalization.
Revised:  The first result is a polynomial normal form based on the canalizing properties of regulatory functions. This polynomial normal form provides a partition of the inputs of the function into canalizing and non-canalizing variables and, within the canalizing ones, we categorize the input variables into layers of canalization.
Edit intent: clarity
Original: Pay-it-forward reciprocity encourages the spread of prosocial behavior. However, existing empirical evidence of pay-it-forward behavior has been largely based on laboratory experiments, which are limited in sample size and external validity. Extending this research, our study uses a natural experiment to examine pay-it-forward reciprocity in a real-life context with a large-scale dataset of 3.4 million users of an online platform. Our natural experiment is enabled by the randomness in the mechanism that WeChat, a Chinese online social networking platform, uses to split an online monetary gift (also known as a "red packet") to its recipients.
Revised: Does receiving a gift encourage the recipient to send more gifts? Causal identification of behavioral contagion is very challenging, especially based on observational data from social networks. Given that the online monetary gift (also known as a "red packet") to its recipients.
Edit intent: coherence
Original:  Our natural experiment is enabled by the randomness in the mechanism that WeChat, a Chinese online social networking platform, uses to split an online monetary gift (also known as a "red packet") to its recipients. Our results show that recipients on average pay forward 10.34 \% of the amount they receive.
Revised:  Our natural experiment is enabled by the randomness in the mechanism that WeChat, a Chinese online social networking platform, uses to split an online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment to identify the causal effect of receiving online red packets on the contagion of gift exchange. Analyzing gifting behavior using a large-scale dataset of 3.4 million WeChat users, we find that recipients on average pay forward 10.34 \% of the amount they receive.
Edit intent: meaning-changed
Original:   We further find that  " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients .
Revised:  Moreover, our analysis shows that recipients' contagion may be driven by different types of reciprocity. We further find that " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients .
Edit intent: meaning-changed
Original:   We further find that  " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients .
Revised:  We further find that the " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients .
Edit intent: fluency
Original:   We further find that  " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients . Our analyses indicate that in a multiple recipient setting, users' pay-it-forward behavior is enforced by a group norm that luckiest draw recipients should send the first subsequent gift and promoted by their distributional social preferences of the random amounts split by the platform.
Revised:  We further find that " Luckiest draw" recipients , or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients , and identify a group norm that luckiest draw recipients should send the first subsequent gift and promoted by their distributional social preferences of the random amounts split by the platform.
Edit intent: clarity
Original:  Our analyses indicate that in a multiple recipient setting, users' pay-it-forward behavior is enforced by a group norm that luckiest draw recipients should send the first subsequent gift and promoted by their distributional social preferences of the random amounts split by the platform. Finally, our study shows that those recipients without any in-group friends do pay it forward, even though their pay-it-forward behavior is less likely to be driven by their reputational concerns among acquaintances. Overall, our work provides insights into mechanisms and conditions that encourage pay-it-forward reciprocity, which have implications for fostering prosocial behavior .
Revised:  Our analyses indicate that in a multiple recipient setting, users' pay-it-forward behavior is enforced by a group norm that luckiest draw recipients should send payment back to the group .
Edit intent: clarity
Original: Does receiving a gift encourage the recipient to send more gifts ? Causal identification of behavioral contagion is very challenging , especially based on observational datafrom social networks. Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment to identify the causal effect of receiving online red packets on the contagion of gift exchange.
Revised: Does receiving a gift encourage the recipient to send more gifts ? Causal identification of contagion is always challenging in observational data; To identify gift contagion, we leverage a natural experiment to identify the causal effect of receiving online red packets on the contagion of gift exchange.
Edit intent: clarity
Original:  Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment to identify the causal effect of receiving online red packets on the contagion of gift exchange.
Revised:  Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment using a large sample of 36 million online red packets on the contagion of gift exchange.
Edit intent: clarity
Original:  Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment to identify the causal effect of receiving online red packets on the contagion of gift exchange. Analyzing gifting behavior using a large-scale dataset of 3.4 million WeChatusers, we find that recipients on average repay 18.29\% of the amount they receive. Moreover, our analysis shows that recipients' contagion may be driven by different types of reciprocity. We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send payment back to the group .
Revised:  Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natural experiment to identify the causal effect of receiving online red packets sent within 174,131 chat groups on WeChat, one of the largest social network services worldwide. Our natural experiment is enabled by WeChat's random gift amount algorithm, with which the amount that a user receives does not depend on her own attributes. We find that, on average, receiving one more dollar causes a recipient to send 18 cents back to the group within the subsequent 24 hours. Moreover, this effect is much stronger for "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send payment back to the group .
Edit intent: meaning-changed
Original:  We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send payment back to the group .
Revised:  We further find thatthe "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm that luckiest draw recipients should send payment back to the group .
Edit intent: meaning-changed
Original:  We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send payment back to the group .
Revised:  We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm according to which the luckiest draw recipients should send payment back to the group .
Edit intent: clarity
Original:  We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send payment back to the group .
Revised:  We further find thatthe "luckiest draw" recipients repay 1.5 times more than other recipients, and identify a group norm that luckiest draw recipients should send the first subsequent red packets. Additionally, we find that gift contagion is affected by in-group friendship network properties, such as the number of in-group friends and the local clustering coefficient .
Edit intent: meaning-changed
Original: Our study seeks to identify the social contagion of in-group gifts: if gifts trigger their recipients to send more gifts subsequently, the actual impact of a gift on group dynamics would be greatly amplified. Causal identification of contagion is always challenging in observational data; To identify gift contagion , we leverage a natural experiment using a large sample of 36 million online red packets sent within 174,131 chat groups on WeChat, one of the largest social network services worldwide .
Revised: Gifts are important instruments for forming bonds in interpersonal relationships. Our study analyzes the phenomenon of gift contagion in online groups. Gift contagion encourages social bonds of prompting further gifts; it may also promote group interaction and solidarity. Using data on 36 million online red packets sent within 174,131 chat groups on WeChat, one of the largest social network services worldwide .
Edit intent: clarity
Original:  To identify gift contagion , we leverage a natural experiment using a large sample of 36 million online red packets sent within 174,131 chat groups on WeChat, one of the largest social network services worldwide .
Revised:  To identify gift contagion , we leverage a natural experiment using a large sample of 36 million online red packet gifts on China's social site WeChat, we leverage a natural experimental design to identify the social contagion of gift giving in online groups .
Edit intent: clarity
Original:  Our natural experiment is enabled by WeChat's random gift amount algorithm, with which the amount that a user receives does not depend on her own attributes. We find that, on average, receiving one more dollar causes a recipient to send 18 cents back to the group within the subsequent 24 hours.
Revised:  Our natural experiment is enabled by the randomization of the gift amount allocation algorithm on WeChat, which addresses the common challenge of causal identifications in observational data. Our study provides evidence of gift contagion: on average, receiving one more dollar causes a recipient to send 18 cents back to the group within the subsequent 24 hours.
Edit intent: meaning-changed
Original:  Moreover, this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Revised:  Decomposing this effect, we find that it is mainly driven by the extensive margin -- more recipients are triggered to send red packets. Moreover, we find that this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Edit intent: meaning-changed
Original:  Moreover, this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Revised:  Moreover, this effect is stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Edit intent: clarity
Original:  Moreover, this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Revised:  Moreover, this effect is much stronger for "luckiest draw" recipients , suggesting the presence of a group norm according to which the luckiest draw recipients should send the first subsequent red packets.
Edit intent: clarity
Original:  Moreover, this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm according to which the luckiest draw recipients should send the first subsequent red packets. Additionally, we find that gift contagion is affected by in-group friendship network properties, such as the number of in-group friends and the local clustering coefficient .
Revised:  Moreover, this effect is much stronger for "luckiest draw" recipients or those who receive the largest share from a red packet, suggesting a group norm regarding the next red packet sender. Finally, we investigate the moderating effects of group- and individual-level social network characteristics on gift contagion as well as the causal impact of receiving gifts on group network structure. Our study has implications for promoting group dynamics and designing marketing strategies for product adoption .
Edit intent: clarity
Original:   Illustrating the formulation of expectile in terms of expected shortfall, we also provide explicit or semi-explicit expressions of expectile  for some classical distributions.
Revised:  We use concentration inequalities to illustrate how the empirical estimation of tail index using expectile versus expected shortfall is better than expectile versus quantile for fat tail distributions. Illustrating the formulation of expectile in terms of expected shortfall, we also provide explicit or semi-explicit expressions of expectile for some classical distributions.
Edit intent: meaning-changed
Original:  Here, I review the existing literature on the cognitive basis of cooperation, altruism, honesty, positive and negative reciprocity, and utilitarianism. For each of these domains, I list a number of open problems that I believe to be crucial to further advance our understanding of the cognitive basis of human sociality. I conclude by making an attempt to introduce a game-theoretical framework URLanize the existing empirical evidence .
Revised:  Here, I review the existing literature on the cognitive basis of cooperation, altruism, honesty, positive and negative reciprocity, and (act) utilitarianism. I conclude by introducing a game-theoretical framework URLanize the existing empirical evidence .
Edit intent: clarity
Original:  This framework seems to be a promising starting point, as it turns out to make predictions thatare qualitatively in line with the experimental data in all but two domains: honesty (when lying harms " abstract others " ) and positive reciprocity.
Revised:  This framework extends Rand and colleagues' Social Heuristics Hypothesis to any one-shot game G. The core assumption of this " abstract others " ) and positive reciprocity.
Edit intent: meaning-changed
Original:  This framework seems to be a promising starting point, as it turns out to make predictions thatare qualitatively in line with the experimental data in all but two domains: honesty (when lying harms " abstract others " ) and positive reciprocity.
Revised:  This framework seems to be a promising starting point, as it turns out to make predictions thatare qualitatively in line with the experimental data in all but two domains: honesty (when lying harms " General Social Heuristics Hypothesis " ) and positive reciprocity.
Edit intent: meaning-changed
Original:  This framework seems to be a promising starting point, as it turns out to make predictions thatare qualitatively in line with the experimental data in all but two domains: honesty (when lying harms " abstract others " ) and positive reciprocity. I tried to keep the review self-contained, exhaustive, and research-oriented. My hope is that it can contribute to bring further attention to this fascinating area of research .
Revised:  This framework seems to be a promising starting point, as it turns out to make predictions thatare qualitatively in line with the experimental data in all but two domains: honesty (when lying harms " abstract others " is that, under intuition, people play a Nash equilibrium of the "real analogue of G", G^{real .
Edit intent: meaning-changed
Original:  usually constrained to the technical idiosyncrasy of the network used . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures  offer a broader and novel spectrum to approach these psychopathologies , outlining the future research on neural networks computational psychiatry, a powerful asset for understanding the inner processes of the human brain .
Revised:  usually constrained to the technical idiosyncrasy of the used network architecture . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures offer a broader and novel spectrum to approach these psychopathologies , outlining the future research on neural networks computational psychiatry, a powerful asset for understanding the inner processes of the human brain .
Edit intent: clarity
Original:  usually constrained to the technical idiosyncrasy of the network used . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures  offer a broader and novel spectrum to approach these psychopathologies , outlining the future research on neural networks computational psychiatry, a powerful asset for understanding the inner processes of the human brain .
Revised:  usually constrained to the technical idiosyncrasy of the network used . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures could offer a broader and novel spectrum to approach these psychopathologies , outlining the future research on neural networks computational psychiatry, a powerful asset for understanding the inner processes of the human brain .
Edit intent: clarity
Original:  usually constrained to the technical idiosyncrasy of the network used . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures  offer a broader and novel spectrum to approach these psychopathologies , outlining the future research on neural networks computational psychiatry, a powerful asset for understanding the inner processes of the human brain .
Revised:  usually constrained to the technical idiosyncrasy of the network used . Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures offer a broader and novel spectrum to approach these psychopathologies . This review emphasizes the power of artificial neural networks for modeling some symptoms of neurological disorders but also calls for further developing these techniques in the field of computational psychiatry .
Edit intent: meaning-changed
Original: The increase in complexity of engineered systems and naturally occurring systems, coupled with increasingly data-driven representations of these systems motivates the need for design of experiment frameworks for nonlinear system identification. In the case of a general nonlinear autonomous system (without inputs or control), designing an experiment for identification relies on the selection of persistently exciting flows and their corresponding initial conditions. This work investigates persistence of excitation conditions for discrete-time nonlinear systems that can be represented using Koopman operators.
Revised: It is hard to identify nonlinear biological models strictly from data, with results that are often sensitive to experimental conditions. Automated experimental workflows and liquid handling enables unprecedented throughput, as well as the capacity to generate extremely large datasets. We seek to develop generalized identifiability conditions for informing the design of automated experiments to discover predictive nonlinear biological models. For linear systems, identifiability is characterized by persistence of excitation conditions. For nonlinear systems, no such persistence of excitation conditions for discrete-time nonlinear systems that can be represented using Koopman operators.
Edit intent: coherence
Original:  This work investigates persistence of excitation conditions for discrete-time nonlinear systems that can be represented using Koopman operators. The Koopman operator presents a linear lifted representation of the evolution of a nonlinear system over a space of observable functions. We use this framework to derive spectral conditions for persistence of excitation, relating classical notions of persistence of excitation to the spectral properties of initial conditions, seen through the lens of Koopman observable functions .
Revised:  This work investigates persistence of excitation conditions exist. We use the input-Koopman operator method to model nonlinear systems and derive identifiability conditions for open-loop systems initialized from a single initial condition. We show that nonlinear identifiability is intrinsically tied to the rank of a given dataset's power spectral density, transformed through the lifted Koopman observable space .
Edit intent: clarity
Original:  We illustrate these concepts on a repressilator circuit , a classical biological system from the field of synthetic biology, to motivate the proper selection of initial conditions. We show that when the rank properties of the flow's spectra are degenerate, the trained Koopman operator does not produce robust predictions on test data .
Revised:  We illustrate these identifiability conditions with a simulated synthetic gene circuit model, the repressilator. We illustrate how rank degeneracy in datasets results in overfitted nonlinear models of the repressilator, resulting in poor predictive accuracy. Our findings provide novel experimental design criteria for discovery of globally predictive nonlinear models of biological phenomena .
Edit intent: clarity