dataesr/scientific-paragraphs-categorization huggingface dataset:
The figure illustrates agreement with respect to changed greenhouse gas concentrations; perturbations in experiment rad-irf in which temperature and/or humidity changes are omitted. (Zhao et al. , 2018) , and for the newly developed RTE+RRTMGP code  (Pincus et al. , 2019)  which is trained on calculations with LBLRTM v12. 8. These parameterizations use recent spectroscopic information and so are likely to be among the parameterizations with the smallest error. Nonetheless, the error in each parameterization is almost always larger than the standard deviation across reference models, indicating differences between parameterizations and all reference models are dominated by parameterization error.
Data Availability Statement All results for RFMIP experiment rad-irf are available on the Earth System Grid Federation (searching for the experiment name is an effective way to find the data). Python scripts and Jupyter notebooks to produce the paper are available at https://github. com/RobertPincus/rfmip-benchmark-paperfigures and are archived online (Zenodo via DOI: 10. 5281/zenodo. 4267190). ERA-Interim data were obtained online (https://www. ecmwf. int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/erainterim). SOCRATES is available from https://code. metoffice. gov. uk/trac/socrates under an open source license but requires a free account from the UK Met Office to access the website. Preliminary data for Table  3  were provided by Tim Andrews and Alejandro Bodas-Salcedo of the UK Met Office but will be derivable through data provided on the Earth System Grid.
The standard also contains the reproducibility clause that forwards the reproducibility issue to language standards. Emerging attention to reproducibility strives to draw more careful attention to the problem by the computer arithmetic community. It has led to the inclusion of error-free transformations (EFTs) for addition and multiplication -to return the exact outcome as the result and the error -to assure numerical reproducibility of floating-point operations, into the revised version of the standard. These mechanisms, once implemented in hardware, will simplify our reproducible algorithms -like the ones used in the ExBLAS  [6] , ReproBLAS  [7] , OzBLAS  [18]  libraries -and boost their performance. There are two approaches that enable the addition of floating-point numbers without incurring round-off errors or with reducing their impact.
To guarantee correctly rounded results of the FPE-based computations, we employ the Add3 algorithm from  [24]  for FPEs of size three and the NearSum algorithm from  [12]  for FPEs of size eight; both may require renormalization before. Listing 3 presents our implementation of the Add3 algorithm; • MPI Bcast() to distribute the result of dot product to the other processes as only master performs rounding. Let us consider this test case: y = a * x + b * y, which is presented in more details in  [26]. The problem with this is that for performance reasons, the C ++ language standard allows compilers to change the execution order of this type of operation. It even allows merging multiplications and summations with fused multiply-add (fma) instructions. This computes a * x + b in a single instruction with only a single rounding operation at the end.
Setup The experiments in this section employed IEEE754 double-precision arithmetic and were carried out in two different clusters: • The MareNostrum4 (MN4) supercomputer at Barcelona Supercomputing Center (BSC): This platform consists of SD530 Compute Racks with an Intel Omni-Path high performance network interconnect. Each node comprises two 24-core Intel Xeon Platinum 8160 processors (2. 10 GHz) and 96 Gbytes of DDR4 RAM. The platform runs the SuSE Linux Enterprise Server operating system. The codes in this platform were compiled using GCC v7. 2. 0, Intel MPI v2018. 1, and MKL v2017. 4. • The Tintorrum cluster at UJI: This is a 8-node cluster, where each node is equipped with two 8-core Intel Xeon(R) E5-2630v3 processors (Haswell-EP) (for a total of 128 cores), running at 2. 4 GHz, with 20 MBytes of L3 on-chip cache (LLC or last level of cache), and with 64 GBytes of DDR3 RAM.
The operating system running in the cluster is Linux version 2. 6. 32-642. 4. 2. el6. centos. plus. x86 64. The codes were compiled with GCC v5. 3. 0, OpenMPI v1. 10. 2, and Intel MKL v2017. 1. For the experimental analysis, we leveraged a sparse (symmetric positive definite) coefficient matrix arising from the finite-difference method of a 3D Poisson's equation with 27 stencil points. The right-hand side vector b in the iterative solvers was always initialized to the product A(1, 1,. , 1) T , and the PCG iteration was started with the initial guess x 0 = 0. The parameter that controls the convergence of the iterative process was set to 10 -8.
In the experiments, we have used the version 3. 1 of this library. Compared with the HPCG benchmark, our regular MPI implementation is composed of the same type of numerical kernels and, therefore, exhibits analogous data access patterns and the arithmetic-to-memory operations ratios. The only difference resides in the implementation of the communications. Concretely, in order to realize the SpMV kernel, we invoke the MPI Allgatherv routine to merge the partial results for all the subvectors. In contrast, HPCG implements an ad-hoc pattern which only sends/ receives the required elements, reducing the communication time. The main drawback of the HPCG alternative is that this communication pattern is optimized for a specific problem, but it may not always provide the best solution for a more general case.
Accuracy and Reproducibility Evaluation In addition to the performance results, we report also the results of the accuracy and reproducibility evaluation. For that, we develop a generator of ill-conditioned matrices. This generator scales the first row and the first column of the matrix so that dot product attains specified condition number and, hence, the matrix. Additionally, we derive a sequential version of the code that relies on the GNU Multiple Precision Floating-Point Reliably (MPFR) library  [30]  1. 00 1. 20   -a C library for multiple (arbitrary) precision floating-point computations on CPUs -as a highly accurate reference implementation. This implementation uses 2,048 bits of accuracy for computing dot product (192 bits for internal product of two floating-point numbers) and performs correct rounding of the computed result to double precision.
We also add the results of the original code on one core/ process to highlight the reproducibility issue. To show these results, we merge two columns of the ExBLAS and Opt results as they are identical. Furthermore, we have also computed the direct error (see Table  4 ) where the difference is even larger: the error is 0x1p+0 on the initial iteration for both MPFR and orig, however the error is completely different (except of the exponent) from the 31st iteration with 0x1. f42fe8p-31 for MPFR and 0x1. ecfb68p-31 for the original version. Note that the results on ExBLAS and Opt are identical to MPFR. We assume that this discrepancy in accuracy and reproducibility becomes larger at scale (more nodes) due to the stronger impact of the topology and reduction trees.
Both strategies deliver identical results to ensure reproducibility of PCG such as in the number of iterations, the intermediate and final residuals, the direct errors, as well as the output vectorsolution. The lightweight reproducible version of PCG outperforms the ExBLAS-based one by 2. 57x on a single node, showing the overhead of roughly 36 %, due to the lower demand for FLOPs and memory. When the communication starts to have stronger impact, both versions show very low overhead compared to the original non-deterministic implementation: 29 % for ExBLAS and 4 % for lightweight on 768 cores of MareNostrum4; 21 % for ExBLAS and 3. 4 % for lightweight on 128 cores of Tintorrum. This is a solid argument to use reproducible PCG at scale. The code is available at https://github. com/riakymch/ReproCG.
Acknowledgment To begin with, we would like to thank the reviewers for their thorough reading of the article as well as their valuable comments and suggestions. This research was partially supported by the  European Union 's  Horizon 2020 research, innovation programme  under the  Marie Skłodowska-Curie  grant agreement via the  Robust  project No. 842528  as well as the Project  HPC-EUROPA3 (INFRAIA-2016-1-730897 ), with the support of the  H2020 EC RIA Programme ; in particular, the author gratefully acknowledges the support of VicencBeltran and the computer resources and technical support provided by  BSC. The researchers from  Universitat Jaume I (UJI)  and  Universidad Politécnica de Valencia (UPV)  were supported by  MINECO  project  TIN2017-82972-R. Maria Barreda  was also supported by the  POSDOC-A/2017/11  project from the  Universitat Jaume I.
We present a digital, freely available, searchable, and evaluated compilation of rate coefficients for the gas-phase reactions of organic compounds with OH, Cl, and NO 3 radicals and with O 3. Although other compilations of many of these data exist, many are out of date, most have limited scope, and all are difficult to search and to load completely into a digitized form. This compilation uses results of previous reviews, though many recommendations are updated to incorporate new or omitted data or address errors, and includes recommendations on many reactions that have not been reviewed previously. The database, which incorporates over 50 years of measurements, consists of a total of 2765 recommended bimolecular rate coefficients for the reactions of 1357 organic substances with OH, 709 with Cl, 310 with O 3 , and 389 with NO 3 , and is much larger than previous compilations.
Many compound types are present in this database, including naturally occurring chemicals formed in or emitted to the atmosphere and anthropogenic compounds such as halocarbons and their degradation products. Recommendations are made for rate coefficients at 298 K and, where possible, the temperature dependences over the entire range of the available data. The primary motivation behind this project has been to provide a large and thoroughly evaluated training dataset for the development of structure-activity relationships (SARs), whose reliability depends fundamentally upon the availability of high-quality experimental data. However, there are other potential applications of this work, such as research related to atmospheric lifetimes and fates of organic compounds, or modelling gas-phase reactions of organics in various environments.
Compendia of kinetic data already exist. Notable among these are the thoroughly evaluated datasets provided by the IUPAC Task Group on Atmospheric Chemical Kinetic Data Evaluation  (Ammann et al. , 2013; Atkinson et al. , 2004 Atkinson et al. , , 2006 Atkinson et al. , , 2007 Atkinson et al. , , 2008;; Crowley et al. , 2010 Crowley et al. , , 2013;; IUPAC, 2019) , the NASA Panel for Data Evaluation  (Burkholder et al. , 2015) , and the Calvert et al. reviews  (Calvert et al. , 2000 (Calvert et al. , , 2002 (Calvert et al. , , 2008 (Calvert et al. , , 2011 (Calvert et al. , , 2015)). The JPL and IUPAC panels are a vital resource, providing detailed evaluations of the major inorganic and organic reactions of importance in atmospheric chemistry, and in fact their reviews of VOC oxidation rate coefficient data (although limited in scope) provide a starting point for our compilation.
The work conducted here should be viewed as complementary to these activities, most closely aligned in scope with the Calvert et al. set of reviews. The NIST Chemical Kinetics Database is an extensive compilation of kinetic data  (Manion et al. , 2015) , which, although it is not evaluated, possesses an extremely large scope. Despite the many useful aspects of these resources, they have several drawbacks, such as the following:   (Micallef and Rodgers, 2014). The size and position of each curve is proportional to the number of species studied with respect to each oxidant, the number of compounds available in each review, and the overlap between these reviews. 1. The frequency with which kinetic data are published is much faster than that with which these data are compiled and reviewed. In the case of IUPAC and JPL, review cycles tend to be ∼ 3-4 years.
2. The number of reaction rates that have been evaluated is considerably smaller than the number that have been determined -in the case of IUPAC and JPL, vastly so. It is therefore inevitable that such evaluations do not currently capture the full chemical diversity available in the experimental literature. 3. The data within these reviews are currently not downloadable in a digital, searchable format. 4. Non-downloadable databases that cannot be accessed offline are subject to downtime (e. g. NIST was recently out of commission for 38 d as a consequence of the 2018-2019 US federal government shutdown). Also, changes can be made to such databases which are not necessarily traceable. The database described here  (McGillen et al. , 2019)  aims to overcome these drawbacks by accounting for the information contained within these previous evaluations and, simultaneously, to augment them by making a new and thorough survey of the chemical kinetics literature.
As shown in Fig. 1 , the size of the database is considerably larger than previous evaluation projects, which is a consequence of merging each of the available evaluations, new measurements becoming available, and the inclusion of measurements that were overlooked previously. In addition to this increase in scope, we plan to periodically update this database as new data become available. This is being carried out as part of the activities of the abovementioned SAR evaluation panel  (Vereecken et al. , 2018). It is intended that this new database will be more agile than these previous efforts, and it will adopt the Earth System Science Data "living data" approach to incorporate new kinetic data that become available and to improve the treatment and description of data herein where necessary.
The rate coefficient (sometimes referred to as a rate constant) is denoted by the symbol "k" and is the constant of proportionality relating the rate of the reaction to the concentration of the reactants. As an example, for the unit stoichiometry reaction OH + CH 4 → CH 3 + H 2 O, the rate of reaction is the rate of loss of OH radicals or CH 4 , or the rate of formation of CH 3 radicals or H 2 O according to Eq. (  1 ): Rate = k[OH] [CH 4 ] = -d[OH]/dt = -d[CH 4 ]/dt = d[CH 3 ]/dt = d[H 2 O]/dt. ( 1 ) The units of bimolecular rate coefficients in this database are cm 3 molecule -1 s -1 , which are those preferred by the atmospheric chemical kinetics community (e. g. Finlayson-Pitts and Pitts, 2000; Seinfeld and Pandis, 2016). Note that "molecule" is not a unit but is typically included for clarity.
(4) It follows that, where data on the branching ratios between these reactive sites are absent, the kinetic information encoded within the total rate coefficient is incomplete. Unfortunately, this is the general state of affairs for the vast majority of reactions contained within the literature, and hence no attempt is made within the framework of the current version of the database to describe branching ratios. There are approximately 800 reactions in the current database for which the Arrhenius equation has been used to describe the temperature dependence. In the majority of cases, temperature-dependent parameters were taken from previous recommendations, but temperature dependence was re-fitted where problems were identified, such as when temperature ranges were truncated to enable the simpler Arrhenius equation to be used, or where not all data had been incorporated into the recommendation.
Data were re-fitted using the extended Arrhenius equation in ∼ 50 cases, all of which were OH reactions. In total, there were 1951 rate coefficients for which only a room temperature rate coefficient was recommended. In the large majority of cases, this was because of an absence of data outside of room temperature. However, in some cases, such as where room temperature determina-Earth Syst. Sci. Data, 12, 1203 Data, 12, -1216 Data, 12, , 2020  https://doi. org/10. 5194/essd-12-1203-2020 tions were in agreement but where temperature dependences were inconsistent, only the room temperature rate coefficient was recommended. The current database does not contain rate coefficients at other temperatures, other than what could be computed by our recommended temperature-dependent expressions within the stated temperature range.
Methods The reviews of IUPAC, JPL, and Calvert et al. (Ammann et al. , 2013; Atkinson et al. , 2004 Atkinson et al. , , 2006 Atkinson et al. , , 2007;; Burkholder et al. , 2015; Calvert et al. , 2000 Calvert et al. , , 2002 Calvert et al. , , 2008 Calvert et al. , , 2011 Calvert et al. , , 2015;; Crowley et al. , 2010 Crowley et al. , , 2013;; IUPAC, 2019)  constituted the starting point of our data compilation effort. Each recommendation provided in these reviews was transcribed into our own database. Where overlap existed between reviews, recommendations were generally consistent, which provided an opportunity to check for errors in transcription or errors in the reviews. Errors identified in published reviews were excluded from our dataset. Following this initial phase of compilation, kinetic data published between 2015 and present were compiled by searching keywords in Google Scholar over these years and transcribing data from the original publications.
Whereas any data published after 2015 cannot be contained in JPL Evaluation Number 18  (Burkholder et al. , 2015)  and  Calvert et al. (2015) , IUPAC can be more up to date owing to the more localized update cycle of this review body. The NIST kinetic database was also interrogated to find data that are contained within their extensive database and absent from the reviews that we considered, although, at the time of writing, it is noted that this database has also received no updates since 2015. Following this review of available literature, further, more general searches of kinetic publications were made for all years, which would be able to locate data that had been overlooked by the extensive reviews of Calvert et al. or the large NIST database. Once all data known to this study were compiled, reviews for individual reactions were made.
There are several possible outcomes from entering data into the database, and these are described in Fig. 3. Some of the decisions in this review process are easy to arrive at objectively, such as whether or not all measurements are consistent, which can be determined by a simple comparison. However, other decisions are more nuanced, such as whether or not a measurement is trustworthy. In this instance many factors can influence this decision, including the following: -Is the measurement technically difficult? -How well was the measurement performed? -Were appropriate tests made? -Is the apparatus suited to measuring this reaction? -Is the measurement generally consistent with analogous reactions? Because each of these questions requires considerable experience and judgement to answer, the review process was conducted in duplicate and occasionally triplicate, such that, if discrepancies between individual reviewers emerged, these discrepancies were discussed and resolved prior to a final review being accepted by the panel.
Since performing detailed evaluations for each reaction in a database of this size is time-consuming, a streamlined approach to the review process was taken, where a reviewer assessed a longlist of rate coefficients and accepted, rejected, or proposed changes to existing values in the unevaluated database. These actions were compared between reviewers, and, where there was unanimous agreement, values were accepted into the database without further consideration. Subsequently, a shortlist of entries was made, where disagreements were encountered. These were then discussed on an individual basis until a resolution had been reached. Although we consider this approach appropriate for our objective of compiling as comprehensive a compilation of evaluated data as possible within the available amount of time and resources, a number of individual reactions are discussed in more detail in the IUPAC, NASA, and Calvert evaluations, and these are noted in our database as reviews where additional information can be obtained.
We therefore consider this work to be complementary to these previous efforts, and, where detailed evaluations exist, readers are directed to the data sheets/notes found within such publications. Where temperature dependence was available for a reaction, the review process can require that further decisions be made. Firstly, if temperature dependence was determined in some measurements but not others, then A factors were normalized to all available data and the measured Arrhenius temperature dependence parameter, B, was taken from an individual study, or an average of several studies if more than one determination was available. In some instances, where general agreement was observed in A factors but major differences in activation energies were reported, we chose not to recommend temperature-dependent parameters.
Secondly, where there are several temperature-dependent studies that span a large range in temperature, and where the temperature dependence can be described adequately by the extended Arrhenius equation (see Eq. 3), an error-weighted linear least squares fit was performed on the entire dataset, and the resultant expression constitutes our recommendation, as shown in Fig. 2 , for example. Finally, if temperature dependence information is available but all data are at temperatures higher than 298 K, then extrapolation is necessary to estimate the rate coefficient at 298 K. If the extrapolation is sufficiently close, i. e. causes the rate coefficient to change by less than a factor of 2 compared to that calculated for the lowest temperature in the measurement range, then the extrapolated 298 K rate coefficient is recommended but with an increased uncertainty assignment.
We give no 298 K rate coefficient recommendation if the change is greater than that, though the extrapolated rate coefficient is provided as an estimate in the comments. This approach is pragmatic, and more exhaustive treatments are possible; we therefore list this as one of the items of ongoing work listed in Sect. 6. The structure of the current database, as well as the information it contains, is summarized in the instruction manual and Supplement that is provided with the database file. The database file is an Excel spreadsheet with tables containing the data and also with worksheets giving information about the database, worksheets, and macros for searching and extracting information from the database. The database itself consists of tables giving information about the compounds used, the kinetic data, the references cited, and a table of compound names and other identifiers.
The reference citations and (where available) URLs for the various references are given in the "References" table. The chemical identifiers used included commonly used names that were taken from the original publications or the NCI database (National Cancer Institute, 2010), and other identifiers such as CAS registry numbers when available. Unique textual identifiers (canonical SMILES, InChI, and InChiKey) were also included, making this database easily searchable, such that kinetic information can be obtained rapidly without knowledge of how the molecule is named within the database. There are many chemical informatics software packages and resources that are available for generating SMILES and InChI codes, both freeware (e. g. ACD/ChemSketch, 2018) and commercial software pack- a Numbers of compounds with rate coefficient entries for this reaction.