wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We also show that on three widely-used folding engines (RNAstructure, Vienna RNAfold, and CONTRAfold), ThreshKnot always outperforms the much more involved MEA algorithm  (1) in structure prediction accuracy, (2) in its capability to predict pseudoknots,  (3) and in its faster running time .
Revised:  We also show that on three widely-used folding engines (RNAstructure, Vienna RNAfold, and CONTRAfold), ThreshKnot always outperforms the much more involved MEA algorithm (1) in structure prediction accuracy, (2) in its capability to predict pseudoknots, (3) its faster runtime and easier implementation .
Edit intent: clarity
Original:  Based on administrative individual data , we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF) , a causal machine learning estimator for multiple programmes .
Revised:  Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests (MCF) , a causal machine learning estimator for multiple programmes .
Edit intent: meaning-changed
Original:  Simulations show that assigning unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness . Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules .
Revised:  Simulations show that 'black-box' rules that reassign unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness . Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules .
Edit intent: meaning-changed
Original:  Simulations show that assigning unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness . Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules .
Revised:  Simulations show that assigning unemployed to programmes that maximise estimated individual gains can considerably improve effectiveness . Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules .
Edit intent: clarity
Original:  Simulations show that assigning unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness . Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules .
Revised:  Simulations show that assigning unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness : up to 20 percent more (less) time spent in (un)employment within a 30 months window. A shallow policy tree delivers a simple rule that realizes about 70 percent of this gain .
Edit intent: meaning-changed
Original: This paper introduces three notions of perfect equilibriumfor games with many players , respectively, in behavioral , mixed and pure strategies. The equivalence between behavioral strategy perfect equilibrium and mixed strategy perfect equilibrium is established. More importantly, it is shown that after the resolution of strategic uncertainty, a mixed strategy perfect equilibrium leads to a pure strategy perfect equilibrium almost surely. Various properties related to limit admissibility are also considered .
Revised: This paper introduces three notions of perfect equilibriumfor games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection, and ex post perfection. These robustness properties strengthen relevant equilibrium results in the large literature on strategic interactions of many agents. Illustrative applications to congestion games and potential games are presented. In the particular case of a congestion game with strictly increasing cost functions, we show that there is a unique equilibrium traffic flow induced by robust perfect equilibria .
Edit intent: meaning-changed
Original: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post  perfection.
Revised: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with a continuum of players, incorporating three types of perturbations . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post perfection.
Edit intent: meaning-changed
Original: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post  perfection.
Revised: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist (in symmetric mixed strategies and in pure strategies) and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post perfection.
Edit intent: meaning-changed
Original: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post  perfection.
Revised: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important properties of admissibility, trembling-hand perfection , and ex post perfection.
Edit intent: clarity
Original: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post  perfection.
Revised: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, aggregate robustness , and ex post perfection.
Edit intent: meaning-changed
Original: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post  perfection.
Revised: This paper proposes a new equilibrium concept "robust perfect equilibrium" for non-cooperative games with many players . Such an equilibrium is shown to exist and satisfy the important behavioral principles of admissibility, trembling-hand perfection , and ex post robust perfection.
Edit intent: meaning-changed
Original:  We compared the use of a traditional model (Random Forest) with  a hierarchical encoder attention-based neural network (HEA) model using two language embeddings based on BERT and BioBERT.
Revised:  We compared the use of a traditional model (Random Forest) with that of a hierarchical encoder attention-based neural network (HEA) model using two language embeddings based on BERT and BioBERT.
Edit intent: clarity
Original:  The HEA BERT and BioBERT models achieved  F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model (  F1-macro = 0.69).
Revised:  The HEA BERT and BioBERT models achieved average F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model ( F1-macro = 0.69).
Edit intent: clarity
Original:  The HEA BERT and BioBERT models achieved  F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model (  F1-macro = 0.69).
Revised:  The HEA BERT and BioBERT models achieved F1-macro scores across all criteria of 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model ( F1-macro = 0.69).
Edit intent: clarity
Original:  The HEA BERT and BioBERT models achieved  F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model (  F1-macro = 0.69).
Revised:  The HEA BERT and BioBERT models achieved F1-macro scores averaging 0.75 and 0.74, respectively, outperforming the Random Forest model ( F1-macro = 0.69).
Edit intent: clarity
Original:  The HEA BERT and BioBERT models achieved  F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model (  F1-macro = 0.69).
Revised:  The HEA BERT and BioBERT models achieved F1-macro scores averaging 0.75 and 0.74, respectively, on all criteria outperforming the Random Forest model ( average F1-macro = 0.69).
Edit intent: clarity
Original:  Similarly,  HEA BERT and BioBERT scored on average 0.8 and 0.81 (F1-micro) vs. 0.76 for the Random Forest model.
Revised:  Similarly, as measured by F-micro, HEA BERT and BioBERT scored on average 0.8 and 0.81 (F1-micro) vs. 0.76 for the Random Forest model.
Edit intent: meaning-changed
Original:  Similarly,  HEA BERT and BioBERT scored on average 0.8 and 0.81 (F1-micro) vs. 0.76 for the Random Forest model.
Revised:  Similarly, HEA BERT and BioBERT scored on average 0.80 and 0.81 (F1-micro) vs. 0.76 for the Random Forest model.
Edit intent: meaning-changed
Original:  To capture the underpinning physics, one-way coupled particles are introduced to make a Lagrangian tracking supplement to the discrete Boltzmann simulation . Detailed morphological information of the flow field and thermodynamic nonequilibrium behavior around the interfaces in a two-miscible-fluid system are delineated.
Revised:  To capture the underpinning physics, one-way coupled particles are introduced to make a Lagrangian tracking supplement to the discrete Boltzmann simulation of RTI in compressible flows. Via marking two types of tracers with different colors, the tracer distribution provides a clear boundary of two fluids during the RTI evolution. Fine structures of the flow and thermodynamic nonequilibrium behavior around the interfaces in a two-miscible-fluid system are delineated.
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Original:  Via a defined local mixedness , from densities of two kinds of particles, we quantitatively captured the appearance position and indicated the intensity of Kelvin-Helmholtz instability.
Revised:  Distribution of tracers in its velocity phase space makes a charming pattern showing quite dense information on the flow behavior, which opens a new perspective for analyzing and accessing significantly deep insights into the flow system. RTI mixing is further investigated via tracer defined local mixedness , from densities of two kinds of particles, we quantitatively captured the appearance position and indicated the intensity of Kelvin-Helmholtz instability.
Edit intent: meaning-changed
Original:  Via a defined local mixedness , from densities of two kinds of particles, we quantitatively captured the appearance position and indicated the intensity of Kelvin-Helmholtz instability. The effects of compressibility and viscosity on mixing are investigated separately .
Revised:  Via a defined local mixedness , from densities of two kinds of particles, we quantitatively captured the appearance position and indicated the intensity of Kelvin-Helmholtz instability is quantitatively captured by mixedness averaged align the direction of the pressure gradient. The role of compressibility and viscosity on mixing are investigated separately .
Edit intent: meaning-changed
Original:  The underlying mechanism of these two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Revised:  The underlying mechanism of the two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Edit intent: fluency
Original:  The underlying mechanism of these two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Revised:  The underlying mechanism of these two-stage effect is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Edit intent: fluency
Original:  The underlying mechanism of these two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Revised:  The underlying mechanism of these two-stage effects is interpreted as the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Edit intent: coherence
Original:  The underlying mechanism of these two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and a "soft" system with high compressibility and/or low viscosity is favorable for the generation of small structures at the late stage.
Revised:  The underlying mechanism of these two-stage effects is interpreted as that a "hard" system with low compressibility and/or high viscosity is beneficial to the development of large structures at the initial stage and the generation of small structures at the late stage.
Edit intent: clarity
Original:  At the late stage, for a fixed time, the field averaged mixedness exponentially decreases with the viscosity , which indicates the existence of a characteristic viscosity \mu_0. The tracer particles make possible to observe finer structures with clear interfaces in the late mixing stage. One can clearly observe the mixing process and distinguish tracer particles from the heavy and light fluids . Results in this paper are helpful for understanding the mechanism of complex compressible flow with Rayleigh-Taylor instability and present references for related particle tracking experiments .
Revised:  At the late stage, for a fixed time, a saturation phenomenon of viscosity is found that further increase of viscosity cannot see an evident decline in mixedness. The mixing statues of heavy and light fluids . Results in this paper are helpful for understanding the mechanism of complex compressible flow with Rayleigh-Taylor instability and present references for related particle tracking experiments .
Edit intent: meaning-changed
Original:  One can clearly observe the mixing process and distinguish tracer particles from the heavy and light fluids . Results in this paper are helpful for understanding the mechanism of complex compressible flow with Rayleigh-Taylor instability and present references for related particle tracking experiments .
Revised:  One can clearly observe the mixing process and distinguish tracer particles from the heavy and light fluids are not synchronous and the mixing of a RTI system is heterogenous. The results are helpful for understanding the mechanism of complex compressible flow with Rayleigh-Taylor instability and present references for related particle tracking experiments .
Edit intent: meaning-changed
Original:  One can clearly observe the mixing process and distinguish tracer particles from the heavy and light fluids . Results in this paper are helpful for understanding the mechanism of complex compressible flow with Rayleigh-Taylor instability and present references for related particle tracking experiments .
Revised:  One can clearly observe the mixing process and distinguish tracer particles from the heavy and light fluids . Results in this paper are helpful for understanding the mechanism of flow and mixing induced by RTI .
Edit intent: clarity
Original:  Inspired by the success of  LinearFold algorithm that computes the MFE structure in linear time, we address this issue by proposing a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities.
Revised:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we address this issue by proposing a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities.
Edit intent: meaning-changed
Original:  Inspired by the success of  LinearFold algorithm that computes the MFE structure in linear time, we address this issue by proposing a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities.
Revised:  Inspired by the success of LinearFold algorithm that computes the MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities.
Edit intent: coherence
Original:  LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32, 753.
Revised:  LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32, 753 (2.5 days vs. 1.3 minutes).
Edit intent: meaning-changed
Original:  Interestingly, although LinearPartition is approximate, it runs in linear time without sacrificing accuracy when base pair probabilities are used to assemble structures , and even leads to a small accuracy improvement on longer families (16S and 23S rRNA  ).
Revised:  Interestingly, although LinearPartition is approximate, the resulting base pairing probabilities are better correlated with the ground truth structures and lead to a small accuracy improvement on longer families (16S and 23S rRNA ).
Edit intent: meaning-changed
Original:  Interestingly, although LinearPartition is approximate, it runs in linear time without sacrificing accuracy when base pair probabilities are used to assemble structures , and even leads to a small accuracy improvement on longer families (16S and 23S rRNA  ).
Revised:  Interestingly, although LinearPartition is approximate, it runs in linear time without sacrificing accuracy when base pair probabilities are used to assemble structures , and even leads to a small accuracy improvement on families with the longest length sequences (16S and 23S rRNA ).
Edit intent: clarity
Original:  Interestingly, although LinearPartition is approximate, it runs in linear time without sacrificing accuracy when base pair probabilities are used to assemble structures , and even leads to a small accuracy improvement on longer families (16S and 23S rRNA  ).
Revised:  Interestingly, although LinearPartition is approximate, it runs in linear time without sacrificing accuracy when base pair probabilities are used to assemble structures , and even leads to a small accuracy improvement on longer families (16S and 23S rRNA ) when used for downstream structure prediction, as well as a substantial improvement on long-distance base pairs (500+ nt apart ).
Edit intent: meaning-changed
Original:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities . LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Revised:  Inspired by the success of our recently proposed LinearFold algorithm that predicts the approximate MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities . LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Edit intent: clarity
Original:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities . LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Revised:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we design a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities . LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Edit intent: clarity
Original:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities . LinearPartition is 256x faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Revised:  Inspired by the success of our recently proposed LinearFold algorithm that computes the MFE structure in linear time, we propose a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base pairing probabilities , which is shown to be orders of magnitude faster than Vienna RNAfold for a sequence with length 15,780, and 2,771x faster than CONTRAfold for a sequence with length 32,753 ( 2.5 days vs. 1.3 minutes ).
Edit intent: coherence