wanyu/IteraTeR_full_sent huggingface dataset:
Original: For the past century, biologists have attempted to identify and document qualitative properties that underlie molecular binding processes in living cells . Cooperativity in the binding processes represents a primary and highly general mechanism for achieving the collective behaviour that emerges in systems-level properties of macromolecules, pathways, cells URLanisms.
Revised: Cooperative binding processes in living cells . Cooperativity in the binding processes represents a primary and highly general mechanism for achieving the collective behaviour that emerges in systems-level properties of macromolecules, pathways, cells URLanisms.
Edit intent: clarity
Original: For the past century, biologists have attempted to identify and document qualitative properties that underlie molecular binding processes in living cells . Cooperativity in the binding processes represents a primary and highly general mechanism for achieving the collective behaviour that emerges in systems-level properties of macromolecules, pathways, cells URLanisms.
Revised: For the past century, biologists have attempted to identify and document qualitative properties that underlie molecular binding processes in living cells represent a primary and highly general mechanism for achieving the collective behaviour that emerges in systems-level properties of macromolecules, pathways, cells URLanisms.
Edit intent: clarity
Original: For the past century, biologists have attempted to identify and document qualitative properties that underlie molecular binding processes in living cells . Cooperativity in the binding processes represents a primary and highly general mechanism for achieving the collective behaviour that emerges in systems-level properties of macromolecules, pathways, cells URLanisms.
Revised: For the past century, biologists have attempted to identify and document qualitative properties that underlie molecular binding processes in living cells . Cooperativity in the binding processes represents a primary and highly general mechanism for achieving the collective behaviour that emerges at the systems-level properties of macromolecules, pathways, cells URLanisms.
Edit intent: clarity
Original: Cooperative binding processes in living cells represent a primary and highly general mechanism for achieving the collective behaviour that emerges at the systems-level properties of macromolecules, pathways, cells URLanisms. Recent progress in robotics and automated techniques for sampling and analyzing complex biological data can reduce statistical uncertainties (or errors) in measuring cooperativity. An identification of the systematic uncertainties that arise from inaccuracy in the measurement processes, however, has been often non-empirical. Here we propose a comprehensive method to quantitatively evaluate the systematic variances computed not only from a computer simulation of live-cell imaging systems, but also image processing and pattern recognition algorithms for biological images .
Revised: We propose a computational method to quantitatively evaluate the systematic variances computed not only from a computer simulation of live-cell imaging systems, but also image processing and pattern recognition algorithms for biological images .
Edit intent: coherence
Original:  We then demonstrate that such non-statistical variances can affect our biological interpretation of cooperativity in a binding system of interest. Within this computational scheme, the biological interpretation can be more objectively evaluated and understood under a specific configuration of the measurement processes
Revised:  We then demonstrate that such non-statistical uncertainties lead to invalid identification of the measured cooperativity. Through this computational scheme, the biological interpretation can be more objectively evaluated and understood under a specific configuration of the measurement processes
Edit intent: clarity
Original:  In an economy with adverse selection, traders have an incentive to buy assets with unknown quality by using cryptocurrency to exploit the higher security of blockchain technology. This induces the demand for the cryptocurrency or access to the blockchain platform, determining the fundamental value of these new digital innovations. We also analytically demonstrate the effect of higher security of the blockchain technology: it leads to wider spreads in prices and qualities of assets traded via blockchain protocol and the traditional cash market. As well, it has a non-linear effect on the fundamental values of the cryptocurrency and blockchain  platform, depending on the severity of underlying adverse selection.
Revised:  In an economy with asymmetric information, the smart contract in the blockchain platform, depending on the severity of underlying adverse selection.
Edit intent: clarity
Original:  As well, it has a non-linear effect on the fundamental values of the cryptocurrency and blockchain  platform, depending on the severity of underlying adverse selection.
Revised:  As well, it has a non-linear effect on the fundamental values of the cryptocurrency and blockchain protocol mitigates uncertainty. Since, as a new trading platform, the blockchain triggers segmentation of market and differentiation of agents in both the sell and buy sides of the market, it recomposes the asymmetric information and generates spreads in asset price and quality between itself and a traditional platform. We show that marginal innovation and sophistication of the smart contract have non-monotonic effects on the trading value in the blockchain platform, depending on the severity of underlying adverse selection.
Edit intent: meaning-changed
Original:  As well, it has a non-linear effect on the fundamental values of the cryptocurrency and blockchain  platform, depending on the severity of underlying adverse selection. The welfare of agents is also derived, and it is shown to be collinear with the fundamental value of cryptocurrency .
Revised:  As well, it has a non-linear effect on the fundamental values of the cryptocurrency and blockchain platform, its fundamental value, the price of cryptocurrency, and consumers' welfare. Moreover, a blockchain manager who controls the level of the innovation of the smart contract has an incentive to keep it lower than the first best when the underlying information asymmetry is not severe, leading to welfare loss for consumers .
Edit intent: meaning-changed
Original: We propose a metric - called Multi-Scale Relevance (MSR) - to score neurons for their prominence in encoding for the animal's behaviour that is being observed in a multi-electrode array recording experiment.
Revised: Neuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions. In this paper we propose a metric - called Multi-Scale Relevance (MSR) - to score neurons for their prominence in encoding for the animal's behaviour that is being observed in a multi-electrode array recording experiment.
Edit intent: clarity
Original: We propose a metric - called Multi-Scale Relevance (MSR) - to score neurons for their prominence in encoding for the animal's behaviour that is being observed in a multi-electrode array recording experiment. The MSR assumes that relevant neurons exhibit a wide variability in their dynamical state, in response to the external stimulus, across different time scales.
Revised: We propose a metric - called Multi-Scale Relevance (MSR) -- to capture the dynamical variability of the activity of single neurons across different time scales.
Edit intent: clarity
Original:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific  tuning curve for neural activity.
Revised:  The MSR is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific tuning curve for neural activity.
Edit intent: meaning-changed
Original:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific  tuning curve for neural activity.
Revised:  It is a non-parametric, fully featureless indicator in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific tuning curve for neural activity.
Edit intent: fluency
Original:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific  tuning curve for neural activity.
Revised:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity without resorting to any a priori covariate or invoking any specific tuning curve for neural activity.
Edit intent: fluency
Original:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific  tuning curve for neural activity.
Revised:  It is a non-parametric, fully featureless indicator , in that it uses only the time stamps of the firing activity , without resorting to any a priori covariate or invoking any specific structure in the tuning curve for neural activity.
Edit intent: clarity
Original:  We test the method on data from freely moving rodents, where we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made.
Revised:  When applied to neural data from the mEC and from the ADn and PoS regions of freely-behaving rodents, we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made.
Edit intent: meaning-changed
Original:  In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded  .
Revised:  In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded and significantly better than the set of neurons with high local variations in their interspike intervals. Given these results, we propose that the MSR can be used as a measure to rank and select neurons for their information content without the need to appeal to any a priori covariate .
Edit intent: meaning-changed
Original: We examine the problem of optimal sparse encoding of sensory stimuli by latent variables in stochastic models. Analyzing restricted Boltzmann machines with a communications theory approach, we search for the minimal model size that correctly conveys the correlations in stimulus patterns in an information-theoretic sense.
Revised: In this work we explore emergent encoding strategies learned by statistical models of sensory coding in noisy spiking networks. Early stages of sensory communication in neural systems can be viewed as encoding channels in the information-theoretic sense.
Edit intent: clarity
Original:  We show that the Fisher information Matrix (FIM) reveals the optimal model size. In larger models the FIM reveals that irrelevant parameters are associated with individual latent variables, displaying a surprising amount of order . For well-fit models, we observe the emergence of statistical criticality as diverging generalized susceptibility of the model. In this case, an encoding strategy is adopted where highly informative , but rare stimuli selectively suppress variability in the encoding units. The information content of the encoded stimuli acts as an unobserved variable leading to criticality. Together, these results can explain the stimulus-dependent variability suppression observed in sensory systems, and suggest a simple, correlation-based measure to reduce the size of artificial neural networks .
Revised:  However, spiking neural populations face constraints not commonly considered in communications theory. Using Restricted Boltzmann machines, we find that networks with sufficient capacity learn to balance precision and noise-robustness in order to adaptively communicate stimuli with varying information content. Mirroring variability suppression observed in sensory systems, highly informative stimuli are encoded with high precision, at the cost of highly variable responses to frequent, hence less informative stimuli. We find that this coding strategy corresponds to statistical criticality in the neural population code, and emerges at model sizes where the input statistics are well captured. These phenomena have well-defined thermodynamic interpretations, and we discuss their connection to prevailing theories of coding and statistical criticality in neural populations .
Edit intent: coherence
Original:  Using solvated alanine dipeptide and Chignolin mini-protein as our test cases, we illustrate how the distance to the Support Vector Machines  decision hyperplane, the output probability estimates from Logistic Regression  , and other classifiers may be used to reversibly sample slow structural transitions.
Revised:  Using solvated alanine dipeptide and Chignolin mini-protein as our test cases, we illustrate how the distance to the Support Vector Machines ' decision hyperplane, the output probability estimates from Logistic Regression , and other classifiers may be used to reversibly sample slow structural transitions.
Edit intent: fluency
Original:  Using solvated alanine dipeptide and Chignolin mini-protein as our test cases, we illustrate how the distance to the Support Vector Machines  decision hyperplane, the output probability estimates from Logistic Regression  , and other classifiers may be used to reversibly sample slow structural transitions.
Revised:  Using solvated alanine dipeptide and Chignolin mini-protein as our test cases, we illustrate how the distance to the Support Vector Machines decision hyperplane, the output probability estimates from Logistic Regression , the outputs from deep neural network classifiers , and other classifiers may be used to reversibly sample slow structural transitions.
Edit intent: meaning-changed
Original:  Such processes have been described by a law attributed to Charles Goodhartor Donald T. Campbell, most pithily phrased as: 'When a measure becomes a target it ceases to be a good measure.' While the original mentions of this lawaddress policy determination or education respectively, we propose it applies to any competitive societal system : Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups) .
Revised:  To paraphrase what has become known as Goodhart's or Campbell's law : Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups) .
Edit intent: clarity
Original:  While the original mentions of this lawaddress policy determination or education respectively, we propose it applies to any competitive societal system : Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups) .
Revised:  While the original mentions of this lawaddress policy determination or education respectively, we propose it applies to any competitive societal system : Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups) , promoting corruption of the measure. However, we lack a coherent theory of such a process.
Edit intent: meaning-changed
Original:  The model combines an effort incentivization mechanism from economic multitasking theory and contest theory with a slower process of cultural evolution  .
Revised:  The model combines an effort incentivization mechanism from economic multitasking theory and contest theory with a slower process of cultural evolution . We find, that an individual level intrinsic motivation towards the societal goal can bound an evolution towards corrupt practices. Overall, the model provides the first sketch of a general theory of proxy based competition in complex societal systems .
Edit intent: meaning-changed
Original:  However, competition generally depends on imperfect proxy measures in order to assess performance. Examples include: in science, the publication count of an author; in healthcare, the number of patients treated; or in business, the profit achieved. Importantly, some practices may optimize proxy performancebut not the actual societal goal. In such cases, individual decisions and cultural practices may shift away from the societal goal and toward the proxy. To paraphrase what has become known as Goodhart 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Revised:  However, competition generally depends on imperfect proxy measures . For instance profit is used to measure value to consumers, patient volumes to measure hospital performance, or the Journal Impact Factor to measure scientific value. Here we note that 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Edit intent: coherence
Original:  To paraphrase what has become known as Goodhart 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Revised:  To paraphrase what has become known as Goodhartany proxy measure in a competitive societal system becomes a target for the competitors, promoting corruption of the measure 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Edit intent: fluency
Original:  To paraphrase what has become known as Goodhart 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Revised:  To paraphrase what has become known as Goodhart, suggesting a general applicability of what is best known as Campbell 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Edit intent: meaning-changed
Original:  To paraphrase what has become known as Goodhart 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Revised:  To paraphrase what has become known as Goodhart 's or Goodhart's Law. Indeed, prominent voices have argued that the scientific reproducibility crisis or inaction to the threat of global warming represent instances of such competition induced corruption. Moreover, competing individuals often report that competitive pressures limit their ability to act according to the societal goal, suggesting lock-in .
Edit intent: meaning-changed
Original:  Here , we construct an agent based model to explore and formalize the basic components and dynamics of proxy based competition. The model combines an effort incentivization mechanism from economic multitasking theoryand contest theorywith a slower process of cultural evolution . We find, that an individual level intrinsic motivation towards the societal goal can bound an evolution towards corrupt practices .
Revised:  Here , we construct an agent based model , integrating insights from complex systems theory, contest theory, behavioral economics and cultural evolution theory. The model reproduces empirically observed patterns at multiple levels. It further suggests that any system is likely to converge towards an equilibrium level of corruption determined by i) the information captured in the proxy and ii) the strength of an intrinsic incentive towards the societal goal can bound an evolution towards corrupt practices .
Edit intent: meaning-changed
Original:  We propose a new bootstrap test on unconditional and conditional Granger-causality  , as well as on their difference, to catch particularly prominent causality cycles . The null hypothesis is that each causality or causality difference is equal to the median across frequencies .
Revised:  We propose a new bootstrap test on unconditional and conditional Granger-causality , as well as on their difference, to catch particularly prominent causality cycles in relative terms. In particular, we consider a stochastic process derived applying independently the stationary bootstrap to the original series. Our null hypothesis is that each causality or causality difference is equal to the median across frequencies .
Edit intent: meaning-changed
Original:  The null hypothesis is that each causality or causality difference is equal to the median across frequencies . In a dedicated simulation study, we prove that our tool is able to disambiguate causalities significantly larger than the median even in presence of a rich causality structure.
Revised:  The null hypothesis is that each causality or causality difference is equal to the median across frequencies computed on that process. In this way, we are able to disambiguate causalities significantly larger than the median even in presence of a rich causality structure.
Edit intent: clarity
Original:  Our results hold until the stationary bootstrap of Politis Romano (1994) is consistent on the underlying stochastic process . By this method, we point out that in the Euro Area money and output co-implied before the financial crisis of 2008, while after the crisis the only significant direction is from money to output with a shortened period .
Revised:  Our results hold until the stationary bootstrap of Politis test shows power one as the process tends to non-stationarity, thus being more conservative than parametric alternatives. As an example, we infer about the relationship between money stock and GDP in the Euro Area money and output co-implied before the financial crisis of 2008, while after the crisis the only significant direction is from money to output with a shortened period .
Edit intent: meaning-changed
Original:  By this method, we point out that in the Euro Area money and output co-implied before the financial crisis of 2008, while after the crisis the only significant direction is from money to output with a shortened period .
Revised:  By this method, we point out that in the Euro Area via our approach, considering inflation, unemployment and interest rates as conditioning variables. We point out that during the period 1999-2017 the money stock aggregate M1 had a significant impact on economic output at all frequencies, while the opposite relationship is significant only at high frequencies .
Edit intent: meaning-changed