wanyu/IteraTeR_full_sent huggingface dataset:
Original: Bidirectional Encoder Representations from Transformers (BERT)models for medical specialties , such as BioBERT and clinicalBERT, have significantly improved in performing biomedical text mining tasks and have enabled extracting valuable information from biomedical literature ;
Revised: Bidirectional Encoder Representations from Transformers (BERT)models for medical specialties , such as bidirectional encoder representations from transformers (BERT), the performance of information extraction from a free text by NLP has significantly improved for both the general domain and medical domain ;
Edit intent: clarity
Original:  however, only English speakers benefit due to the significant scarcity of high-quality medical documents, such as PubMed, in each language. Therefore, we propose a method to train a high-performance BERT model using a small corpus . We introduce the method to train a BERT model on a small medical corpus both in English and in Japanese , and we present the evaluation of each model in terms of the biomedical language understanding evaluation (BLUE) benchmark and the medical document classification task in Japanese, respectively.
Revised:  however, it is difficult to train specific BERT models that perform well for domains in which there are few publicly available databases of high quality and large size. We hypothesized that this problem can be addressed by up-sampling a domain-specific corpus and using it for pre-training with a larger corpus in a balanced manner. Our proposed method consists of a single intervention with one option: simultaneous pre-training after up-sampling and amplified vocabulary. We conducted three experiments and evaluated the resulting products. We confirmed that our Japanese medical BERT outperformed conventional baselines and the other BERT models in terms of the medical document classification task and that our English BERT pre-trained using both the general and medical-domain corpora performed sufficiently well for practical use in terms of the biomedical language understanding evaluation (BLUE) benchmark and the medical document classification task in Japanese, respectively.
Edit intent: meaning-changed
Original:  We introduce the method to train a BERT model on a small medical corpus both in English and in Japanese , and we present the evaluation of each model in terms of the biomedical language understanding evaluation (BLUE) benchmark and the medical document classification task in Japanese, respectively. After confirming their satisfactory performances, we applied our method to develop a modelcomparable to the publicly available models. OuBioBERT, short for Bidirectional Encoder Representations from Transformers for Biomedical Text Mining by Osaka University, achieved the best score in terms of the BLUE benchmark .
Revised:  We introduce the method to train a BERT model on a small medical corpus both in English and in Japanese , and we present the evaluation of each model in terms of the biomedical language understanding evaluation (BLUE) benchmark . Moreover, our enhanced biomedical BERT model, in which clinical notes were not used during pre-training, showed that both the clinical and biomedical scores of the BLUE benchmark .
Edit intent: coherence
Original:  OuBioBERT, short for Bidirectional Encoder Representations from Transformers for Biomedical Text Mining by Osaka University, achieved the best score in terms of the BLUE benchmark . The total score is 1.1 points above that of BioBERT and 0.3 points above that of the ablated model trained without our proposed method.
Revised:  OuBioBERT, short for Bidirectional Encoder Representations from Transformers for Biomedical Text Mining by Osaka University, achieved the best score in terms of the BLUE benchmark were 0.3 points above that of the ablated model trained without our proposed method.
Edit intent: clarity
Original: Materials with tunable mechanical properties are ubiquitous in biology and engineering, such as muscle , the cytoskeleton, soft robotic actuators, and magnetorheological fluids. Their functionality arises through an external signal that modulates intrinsic mechanical properties, like neural spikes in muscle. However, current rheological methods assume approximately invariant mechanical properties during measurement, and thus cannot be used for characterizing the rheology of tunable materials.
Revised: This paper proposes a hypothesis for the tunable rheology of skeletal muscle and thus cannot be used for characterizing the rheology of tunable materials.
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Original:  However, current rheological methods assume approximately invariant mechanical properties during measurement, and thus cannot be used for characterizing the rheology of tunable materials. Here, we develop a geometric framework for characterizing tunable materials by combining classical oscillatory rheology that uses Lissajous force-length loops to characterize non-tunable materials, with the technique of work loops that is used to study muscle's work output under varying stimulation.
Revised:  However, current rheological methods assume approximately invariant mechanical properties during measurement, and tests it using published datasets and simulations. Skeletal muscle's rheology, how it deforms under forces, is neurally modulated and crucial for animal movement. Muscle's force-length loops to characterize non-tunable materials, with the technique of work loops that is used to study muscle's work output under varying stimulation.
Edit intent: meaning-changed
Original:  Here, we develop a geometric framework for characterizing tunable materials by combining classical oscillatory rheology that uses Lissajous force-length loops to characterize non-tunable materials, with the technique of work loops that is used to study muscle's work output under varying stimulation. We derive the force-length loop under varying stimulation by splicing Lissajous loops obtained under constant stimulation .
Revised:  Here, we develop a geometric framework for characterizing tunable materials by combining classical oscillatory rheology that uses Lissajous force-length response is well-studied under fixed and time-varying stimulation. Under fixed stimulation, oscillatory force measurements characterize muscle rheology using dynamic material moduli. Under time-varying stimulation, work loops characterize work production and absorption using force-length loop under varying stimulation by splicing Lissajous loops obtained under constant stimulation .
Edit intent: clarity
Original:  We derive the force-length loop under varying stimulation by splicing Lissajous loops obtained under constant stimulation . This splicing approach captures the force-length loop shapes in muscle that are not seen in non-tunable materials, and yields a nondimensional parametrization for the space of possible responses of tunable materials .
Revised:  We derive the force-length curves obtained under periodic length oscillations. But unlike fixed-stimulus measurements, work loops exhibit unusual but functionally critical features like work-producing loop reversals and self-intersections. We tested the hypothesis that work loops emerge by splicing the rheological responses obtained under fixed stimulation and found that it accurately predicts the loops in experimental data on sculpin skeletal muscle and in numerical sarcomere simulations. Thus, classical rheological loops and splicing underlie the emergent shape of muscle work loops under steady dynamical conditions .
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Original: Information is key during a crisis such as the  current COVID-19 pandemic as it greatly shapes people opinion, behaviour and even their psychological state. It has been acknowledged from the Secretary-General of the United Nations that the infodemic of misinformation is an important secondary crisis produced by the pandemic.
Revised: Information is key during a crisis such as the current COVID-19 pandemic as it greatly shapes people opinion, behavior and their psychology. Infodemic of misinformation is an important secondary crisis produced by the pandemic.
Edit intent: clarity
Original:  We then assess the resulting topology of clusters of leaders . Although this tool may be used for surveillance of individuals, we propose it as the basis for a constructive application to empower users with a positive influence in the collective behaviour of the network and the propagation of information.
Revised:  We then assess the resulting topology of clusters of leaders visually. We propose this tool to be the basis for a constructive application to empower users with a positive influence in the collective behaviour of the network and the propagation of information.
Edit intent: clarity
Original:  Although this tool may be used for surveillance of individuals, we propose it as the basis for a constructive application to empower users with a positive influence in the collective behaviour of the network and the propagation of information.
Revised:  Although this tool may be used for surveillance of individuals, we propose it as the basis for a system to detect and empower users with a positive influence in the collective behaviour of the network and the propagation of information.
Edit intent: clarity
Original:  Although this tool may be used for surveillance of individuals, we propose it as the basis for a constructive application to empower users with a positive influence in the collective behaviour of the network and the propagation of information.
Revised:  Although this tool may be used for surveillance of individuals, we propose it as the basis for a constructive application to empower users with a positive influence in the collective behavior of the network and the propagation of information.
Edit intent: fluency
Original:  We study this problem in the {\em k-machine model}, Note that parameter k stands for the number of machines in the k-machine model and is independent of K-nearest points. a model for distributed large-scale data.
Revised:  We study this problem in the {\em k-machine model}, (Note that parameter k stands for the number of machines in the k-machine model and is independent of K-nearest points.) a model for distributed large-scale data.
Edit intent: coherence
Original:  \% This is due to the existence of a lower bound of \Omega(\log n) communication rounds for finding the {\em median} of 2n elements distributed evenly among two processors by Rodeh rodeh.
Revised:  (Algorithms that use only comparison operations (\leq, \geq, =) between elements to distinguish the ordering among them). This is due to the existence of a lower bound of \Omega(\log n) communication rounds for finding the {\em median} of 2n elements distributed evenly among two processors by Rodeh rodeh.
Edit intent: meaning-changed
Original: The objective is to provide an Al\`os type decomposition formula and an approximate option pricing formula for the Barndorff-Nielsen and Shephard model: an Ornstein-Uhlenbeck type stochastic volatility model driven by a subordinator without drift.
Revised: The objective is to provide an Al\`os type decomposition formula of call option prices for the Barndorff-Nielsen and Shephard model: an Ornstein-Uhlenbeck type stochastic volatility model driven by a subordinator without drift.
Edit intent: clarity
Original:  As far as we know, this is the first result on the Al\`os type decomposition formula for models with infinite active jumps . Moreover, investigating the rate of convergence as the time to maturity tends to 0 for each term in the obtained decomposition formula, we shall present an approximate option pricing formula, and implement numerical experiments, which show that our approximation formula is effective for in-the-money options .
Revised:  As far as we know, this is the first result on the Al\`os type decomposition formula for models with infinite active jumps .
Edit intent: coherence
Original:  In this paper, we propose %DIFDELCMD < \modele%%%  , an end-to-end structural temporal Graph Neural Network model for detecting anomalous edges in dynamic graphs.
Revised:  In this paper, we propose %DIFDELCMD < \modele%%% StrGNN , an end-to-end structural temporal Graph Neural Network model for detecting anomalous edges in dynamic graphs.
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Original:  In both cases, we show that our approximating family is faster to calibrate than either mean field or structured Gaussian approximations, and that the gains in posterior estimation accuracy are considerable .
Revised:  In both cases, we show that our approximating family is faster to calibrate than either mean field or structured Gaussian approximations, and faster than Markov chain Monte Carlo. Last, we show how to implement data sub-sampling in variational inference for our approximation, which can lead to a further reduction in computation time .
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Original:  We focus on two transfer mechanisms using the joint numerical space for many languages as implemented in the LASER library : the transfer of trained models, and expansion of training sets with instances from other languages .
Revised:  We focus on two transfer mechanisms that recently show superior transfer performance. The first mechanism uses the trained models whose input is the joint numerical space for many languages as implemented in the LASER library : the transfer of trained models, and expansion of training sets with instances from other languages .
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Original:  Our experiments show that the transfer of models between similar languages is sensible, while dataset expansion did not increase the predictive performance .
Revised:  Our experiments show that the transfer of models between similar languages is sensible, even with no target language data. The performance of cross-lingual models obtained with the multilingual BERT and LASER library is comparable, and the differences are language-dependent. The transfer with CroSloEngual BERT, pretrained on only three languages, is superior on these and some closely related languages .
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Original: An approach for building mixed-initiative tools for the procedural generation of game levels  using interactive evolutionary optimisation is introduced. A tool is created based on this approach which (a) is focused on supporting the designer to explore the design space and (b) only requires the designer to interact with it by designing levels.
Revised: An approach for building mixed-initiative tools for the procedural generation of game levels using interactive evolutionary optimisation was designed for this study which (a) is focused on supporting the designer to explore the design space and (b) only requires the designer to interact with it by designing levels.
Edit intent: clarity
Original:  This results in a number of suggestions which are presented to the designer, who can then edit them providing the system with valuable designer feedback. The effectiveness of this approach to create levels with similar level design patterns to a target is illustrated through a series of algorithm driven benchmark tests. To test the mixed-initiative aspect of the tool a triple-blind mixed-method, user study was conducted.
Revised:  A rigorous user study was designed which compared the experiences of designers using the mixed-initiative aspect of the tool a triple-blind mixed-method, user study was conducted.
Edit intent: clarity
Original:  To test the mixed-initiative aspect of the tool a triple-blind mixed-method, user study was conducted. When compared to a control group, provided with random level suggestions throughout the design process, the mixed-initiative approach increased engagement in the level design task and was effective in inspiring new ideas and design directions.
Revised:  To test the mixed-initiative tool to designers who were given a tool which provided completely random level suggestions throughout the design process, the mixed-initiative approach increased engagement in the level design task and was effective in inspiring new ideas and design directions.
Edit intent: clarity
Original:  We aim to provide a review that demystifies dynamic networks, introduces dynamic graph neural networks (DGNNs) and appeals to researchers with a background in either network science or data science. We contribute: (i) a comprehensive dynamic network taxonomy, (ii) a survey of dynamic graph neural networks and (iii) an overview of how dynamic graph neural networks can be used for dynamic link prediction.
Revised:  We aim to provide a review that demystifies dynamic networks, introduces dynamic graph neural networks , this work is split into two main parts. First, to address the ambiguity of the dynamic network terminology we establish a foundation of dynamic networks with consistent, detailed terminology and notation. Second, we present a comprehensive survey of dynamic graph neural networks can be used for dynamic link prediction.
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Original:  While manipulated fire return interval and seasonality moderated both fire spread rate and intensity, their overall effects were low in comparison with meteorological (hydrological and climatic) variables  . Predicting fire spread rate and intensity has been a poor endeavour thus far and we show that more data of the variables already monitored would not result in higher predictive accuracy.
Revised:  While manipulated fire return interval and seasonality moderated both fire spread rate and intensity, their overall effects were low in comparison with meteorological (hydrological and climatic) variables . The variables with the highest feature importance regarding fire spread rate resulted in fuel moisture with 21\%, relative humidity with 15\%, wind speed with 14\%, and last years rainfall with 14\%. The variables with the highest feature importance regarding fire intensity included fuel load with 21.5\%, fuel moisture with 16.5\%, relative humidity with 12.5\%, air temperature with 12.5\%, and rainfall with 12.5\% . Predicting fire spread rate and intensity has been a poor endeavour thus far and we show that more data of the variables already monitored would not result in higher predictive accuracy.
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Original: We present the first succinct  data structure for ordinal trees that supports the mapping between the preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.
Revised: We present the first succinct distance oracles for (unweighted) interval graphs and related classes of graphs, using a novel succinct data structure for ordinal trees that supports the mapping between the preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.
Edit intent: meaning-changed
Original: We present the first succinct  data structure for ordinal trees that supports the mapping between the preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.
Revised: We present the first succinct data structure for ordinal trees that supports the mapping between preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.
Edit intent: fluency
Original:  It also provides constant-time support for all the operations provided by different approaches in previous work, as well as new operations that allow us to retrieve the last internal node before or the firstinternal node after a given node in a level-order traversal .
Revised:  Our distance oracles for interval graphs also support navigation queries -- testing adjacency, computing node degrees, neighborhoods, and shortest paths -- all in optimal time. Our technique also yields optimal distance oracles for proper interval graphs (unit-interval graphs) and circular-arc graphs. Our tree data structure supports all operations provided by different approaches in previous work, as well as new operations that allow us to retrieve the last internal node before or the firstinternal node after a given node in a level-order traversal .
Edit intent: meaning-changed
Original:  It also provides constant-time support for all the operations provided by different approaches in previous work, as well as new operations that allow us to retrieve the last internal node before or the firstinternal node after a given node in a level-order traversal .
Revised:  It also provides constant-time support for all the operations provided by different approaches in previous work, as well as mapping to and from level-order ranks and retrieving the last (first) internal node before (after) a given node in a level-order traversal .
Edit intent: meaning-changed
Original:  It also provides constant-time support for all the operations provided by different approaches in previous work, as well as new operations that allow us to retrieve the last internal node before or the firstinternal node after a given node in a level-order traversal . This new representation gives us the functionality needed to design the first succinct distance oracles for interval graphs, proper interval graphs and k-proper/k-improper interval graphs .
Revised:  It also provides constant-time support for all the operations provided by different approaches in previous work, as well as new operations that allow us to retrieve the last internal node before or the firstinternal node after a given node in a level-order traversal , all in constant time .
Edit intent: clarity
Original: One of the most popular narratives about the evolution of law is its perpetual growth in size and complexity.
Revised: While a large number of informal factors influence how people interact, modern societies rely upon law as a primary mechanism to formally control human behaviour. How legal rules impact societal development depends on the interplay between two types of actors: the people who create the rules and the people to which the rules potentially apply. We hypothesise that an increasingly diverse and interconnected society might create increasingly diverse and interconnected rules, and assert that legal networks provide a useful lens through which to observe the interaction between law and society. To evaluate these propositions, we present a novel and generalizable model of statutory materials as multidimensional, time-evolving document networks. Applying this model to the most popular narratives about the evolution of law is its perpetual growth in size and complexity.
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Original: One of the most popular narratives about the evolution of law is its perpetual growth in size and complexity. We confirm this claim quantitatively for the federal legislation of two industrialised countries, finding impressive expansion in the laws of Germany and the United States over the past two and a half decades.
Revised: One of the federal legislation of two industrialised countries, finding impressive expansion in the laws of Germany and the United States over the past two and a half decades.
Edit intent: clarity
Original: We propose Tapestry , a novel approach to pooled testing with application to COVID-19 testing with quantitative  Polymerase Chain Reaction ( PCR ) that can result in shorter testing time and conservation of reagents and testing kits.
Revised: We propose `Tapestry' , a novel approach to pooled testing with application to COVID-19 testing with quantitative Polymerase Chain Reaction ( PCR ) that can result in shorter testing time and conservation of reagents and testing kits.
Edit intent: fluency
Original: We propose Tapestry , a novel approach to pooled testing with application to COVID-19 testing with quantitative  Polymerase Chain Reaction ( PCR ) that can result in shorter testing time and conservation of reagents and testing kits.
Revised: We propose Tapestry , a novel approach to pooled testing with application to COVID-19 testing with quantitative Reverse Transcription Polymerase Chain Reaction ( PCR ) that can result in shorter testing time and conservation of reagents and testing kits.
Edit intent: meaning-changed