wanyu/IteraTeR_full_sent huggingface dataset:
Original:  (i)  centralization of the social influence network , and (ii) the features of the estimation context---i .e., the distribution of the initial (pre-influence) estimates . Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and /or have a high likelihood of committing egregious errors .
Revised:  (i) centralization of the social influence network , and (ii) the distribution of the initial, individual estimates, i .e., the distribution of the initial (pre-influence) estimates . Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and /or have a high likelihood of committing egregious errors .
Edit intent: meaning-changed
Original:  (i)  centralization of the social influence network , and (ii) the features of the estimation context---i .e., the distribution of the initial (pre-influence) estimates . Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and /or have a high likelihood of committing egregious errors .
Revised:  (i) centralization of the social influence network , and (ii) the features of the estimation context---i .e., the estimation context . Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and /or have a high likelihood of committing egregious errors .
Edit intent: clarity
Original:  (i)  centralization of the social influence network , and (ii) the features of the estimation context---i .e., the distribution of the initial (pre-influence) estimates . Specifically, we find that centralized influence is desirable in situations where a crowd is predisposed to overestimation bias and /or have a high likelihood of committing egregious errors .
Revised:  (i) centralization of the social influence network , and (ii) the features of the estimation context---i .e., the distribution of the initial (pre-influence) estimates . Specifically, we propose a feature of the estimation context that measures the suitability of the crowd to benefit from influence centralization and show its significant predictive powers empirically .
Edit intent: coherence
Original:  By adopting a framework that integrates both the structure of  social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom .
Revised:  By adopting a framework that integrates both the structure of the social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom .
Edit intent: fluency
Original:  By adopting a framework that integrates both the structure of  social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom .
Revised:  By adopting a framework that integrates both the structure of social influence and the estimation context, we bring previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom .
Edit intent: clarity
Original:  By adopting a framework that integrates both the structure of  social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of influence centralization on the quality of crowd wisdom .
Revised:  By adopting a framework that integrates both the structure of social influence and the estimation context, we bring the previously conflicting results under one theoretical framework and clarify the effects of social influence on the wisdom of crowds .
Edit intent: clarity
Original:  [1] as an argument to show that causal structure theories (CST) like IIT are either falsified or outside the realm of science. In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Revised:  [1] 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Edit intent: coherence
Original:  In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Revised:  In their recent paper %DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Edit intent: fluency
Original:  In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Revised:  In their recent paper 2%DIFDELCMD < ]%%% 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Edit intent: fluency
Original:  In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Revised:  In their recent paper 2%DIFDELCMD < ]%%% , %DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Edit intent: coherence
Original:  In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , the authors mathematically formalized the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Revised:  In their recent paper 2%DIFDELCMD < ]%%% , 3%DIFDELCMD < ]%%% , Kleiner and Hoel introduced a formal mathematical model of the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space.
Edit intent: meaning-changed
Original:  However in this note the author identifies the shortcomings in the formulation of the substitution argument and explains why it's claims about functionalist theoriesare wrong ] .
Revised:  However in this note the author identifies the shortcomings in the formulation of the substitution argument and explains why it's claims about functionalist theoriesare wrong ], allowing us to distinguish between different types of variation. Motivated by examples from neural networks, state machines and Turing machines, we will prove that substitutions do not exist for a very broad class of Level-1 functionalist theories, rendering them immune to the aforementioned substitution argument .
Edit intent: meaning-changed
Original:  Pathologists routinely attempt to decipher the site of origin using extensive immunohistochemical staining, however, the rate of identification remains low. Modern cancer therapeutics including immune checkpoint inhibitor therapies are specific to the primary tumor hence broad-spectrum chemotherapy remains the standard-of-care for CUP patients\mbox{%DIFAUXCMD massard2011carcinomas .
Revised:  This poses a significant challenge since modern therapeutics such as chemotherapy regimen and immune checkpoint inhibitors are specific to the primary tumor hence broad-spectrum chemotherapy remains the standard-of-care for CUP patients\mbox{%DIFAUXCMD massard2011carcinomas .
Edit intent: clarity
Original:  However, genomic testing  lacks clinical penetration in low resource settings and may not be available at scale for every patient. Here we show that deep learning-based weakly supervised and multi-task computational pathology on H E slides can be used to determine the metastatic status and site of origin for tumors of unknown primary .
Revised:  However, genomic testing lacks clinical penetration in low resource settings . Herein, to overcome these challenges, we present a deep learning-based weakly supervised and multi-task computational pathology on H E slides can be used to determine the metastatic status and site of origin for tumors of unknown primary .
Edit intent: coherence
Original:  Here we show that deep learning-based weakly supervised and multi-task computational pathology on H E slides can be used to determine the metastatic status and site of origin for tumors of unknown primary .
Revised:  Here we show that deep learning-based weakly supervised and multi-task computational pathology on H computational pathology algorithm-TOAD-that can provide a differential diagnosis for CUP using routinely acquired histology slides .
Edit intent: meaning-changed
Original:  We used 17,486 gigapixel whole slide images  spread over 18 URLans for training a multi-task deep model to simultaneously identify  primary or metastatic status and site of origin.
Revised:  We used 17,486 gigapixel whole slide images with known primaries spread over 18 URLans for training a multi-task deep model to simultaneously identify primary or metastatic status and site of origin.
Edit intent: meaning-changed
Original:  We used 17,486 gigapixel whole slide images  spread over 18 URLans for training a multi-task deep model to simultaneously identify  primary or metastatic status and site of origin.
Revised:  We used 17,486 gigapixel whole slide images spread over 18 common origins to train a multi-task deep model to simultaneously identify primary or metastatic status and site of origin.
Edit intent: clarity
Original:  We used 17,486 gigapixel whole slide images  spread over 18 URLans for training a multi-task deep model to simultaneously identify  primary or metastatic status and site of origin.
Revised:  We used 17,486 gigapixel whole slide images spread over 18 URLans for training a multi-task deep model to simultaneously identify the tumor as primary or metastatic status and site of origin.
Edit intent: meaning-changed
Original:  We used 17,486 gigapixel whole slide images  spread over 18 URLans for training a multi-task deep model to simultaneously identify  primary or metastatic status and site of origin.
Revised:  We used 17,486 gigapixel whole slide images spread over 18 URLans for training a multi-task deep model to simultaneously identify primary or metastatic and predict its site of origin.
Edit intent: clarity
Original:  We tested our model on an internal test set of 4,932 cases  and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 and our external test set of 662 cases from 202 different hospitals  achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Revised:  We tested our model on an internal test set of 4,932 cases with known primaries and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 and our external test set of 662 cases from 202 different hospitals achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Edit intent: meaning-changed
Original:  We tested our model on an internal test set of 4,932 cases  and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 and our external test set of 662 cases from 202 different hospitals  achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Revised:  We tested our model on an internal test set of 4,932 cases and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 while on our external test set of 662 cases from 202 different hospitals achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Edit intent: coherence
Original:  We tested our model on an internal test set of 4,932 cases  and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 and our external test set of 662 cases from 202 different hospitals  achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Revised:  We tested our model on an internal test set of 4,932 cases and achieved a top-1 accuracy of 0.84, a top-3 accuracy of 0.94 and our external test set of 662 cases from 202 different hospitals , it achieved a top-1 and top-3 accuracy of 0.79 and 0.93 respectively.
Edit intent: coherence
Original:  Our proposed method can be used as a diagnostic mechanism in contrast with or in lieu of immunohistochemical staining and may also reduce the occurrence of CUP cases .
Revised:  Our proposed method can be used as an assistive tool to assign differential diagnosis to complicated metastatic and CUP cases and could be used in conjunction with or in lieu of immunohistochemical staining and may also reduce the occurrence of CUP cases .
Edit intent: meaning-changed
Original: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Revised: We consider the Pavlovian eyeblink conditioning (EBC) via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Edit intent: clarity
Original: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Revised: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) . The influence of various temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Edit intent: coherence
Original: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Revised: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Edit intent: clarity
Original: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells .
Revised: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC is investigated in a cerebellar network where the connection probability p_c from Golgi to GR cells .
Edit intent: clarity
Original: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to GR cells . For an optimal value of p_c^*~(=0.029), individual GR cells exhibit diverse spiking patterns which are well- or ill-matched with the unconditioned stimulus.
Revised: We consider the Pavlovian eyeblink conditioning (EBC) in the cerebellum via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff) , and investigate the effect of diverse temporal recoding of granule (GR) cells on the EBC by varying the connection probability p_c from Golgi to granule cells is changed. In an optimal case of p_c^*~(=0.029), individual GR cells exhibit diverse spiking patterns which are well- or ill-matched with the unconditioned stimulus.
Edit intent: clarity
Original:  Then, these diversely-recoded signals via parallel-fibers (PFs) from the GR cells are effectively depressed by the error-teaching signals via climbing fibers (CFs) from the inferior olive. Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Revised:  Then, these variously-recoded signals are fed into the Purkinje cells (PCs) through parallel-fibers (PFs). In the case of well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Edit intent: clarity
Original:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Revised:  Synaptic weights at well-matched PF-PC synapses, their synaptic weights are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Edit intent: clarity
Original:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Revised:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed through strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Edit intent: clarity
Original:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Revised:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) . On the other hand, practically no LTD occurs at ill-matched PF-PC synapses.
Edit intent: coherence
Original:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs at ill-matched PF-PC synapses.
Revised:  Synaptic weights at well-matched PF-Purkinje cell (PC)synapses of active GR cells are strongly depressed via strong long-term depression (LTD) , while practically no LTD occurs for the ill-matched PF-PC synapses.
Edit intent: clarity
Original:  This kind of "effective" depression at  PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Revised:  This type of "effective" depression at PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Edit intent: clarity
Original:  This kind of "effective" depression at  PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Revised:  This kind of "effective" depression at the PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Edit intent: fluency
Original:  This kind of "effective" depression at  PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Revised:  This kind of "effective" depression at PF-PC synapses coordinates firings of PCs effectively, which then make effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Edit intent: clarity
Original:  This kind of "effective" depression at  PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which evokes conditioned response (CR;
Revised:  This kind of "effective" depression at PF-PC synapses coordinates firings of PCs effectively, which then exert effective inhibitory coordination on cerebellar nucleus neuron [which elicits conditioned response (CR;
Edit intent: clarity
Original: We propose a new regularisation strategy within the classical ensemble Kalman inversion (EKI) framework for estimating parameters in PDEs. The regularisation strategy consists of: (i) an adaptive choice for the regularisation /inflation parameter in the update formula in EKI, and (ii) criteria for the early stopping of the scheme.
Revised: We propose a new regularisation strategy within the classical ensemble Kalman inversion (EKI) framework . The strategy consists of: (i) an adaptive choice for the regularisation /inflation parameter in the update formula in EKI, and (ii) criteria for the early stopping of the scheme.
Edit intent: clarity
Original:  The proposed approach is aimed at providing EKI with computational efficiency and robustness for addressing problemswhere the unknown is a heterogeneous physical property with possibly sharp discontinuities arising from the presence of anomalies/defects. In these settings, for EKI to produce accurate estimates of the truth, the unknown needs to be suitably characterised via a parameterisation that often increases the complexity of the identification problem .
Revised:  We motivate our approach using the interpretation of EKI as a Gaussian approximation in the Bayesian tempering setting for inverse problems. We show that our parameter choice controls the symmetrised Kulback-Leibler divergence between consecutive tempering measures. We further motivate our choice using a heuristic statistical discrepancy principle. We test our framework using electrical impedance tomography with the complete electrode model. Parameterisations of the unknown conductivity are employed which enable us to characterise both smooth or a discontinuous (piecewise-constant) fields .
Edit intent: meaning-changed
Original:  We test our framework using various parameterisations including one that combines a truncated Whittle-Matern (WM) level-set function with other WM fields to characterise spatial variability of the physical property on each region. We use these parameterisations to solve PDE-constrained identification problems arising in (i) medical imaging where the aim is to detect the existence and properties of diseased tissue and (ii) non-destructive testing (NDT) of materials from data collected during manufacturing processes. We provide comparisons against a standard method  and demonstrate that the proposed method is  viable choice to address computational efficiency of EKI in practical/operational settings.
Revised:  We compare the proposed technique with a standard method and demonstrate that the proposed method is viable choice to address computational efficiency of EKI in practical/operational settings.
Edit intent: coherence