dataesr/scientific-paragraphs-categorization huggingface dataset:
Introduction High-precision roundness measurement machines are widely used in industry for calibrating cylindrical parts. The common architecture of such machines comprises a sensitive tactile probe (1) fixed to a vertical translating slide (2) via a horizontal arm  (3). The cylindrical part is mounted on a precision rotating air-bearing spindle (4) (Fig. 1 ), aligned along the vertical axis and rotated with respect to the fixed probe. The horizontal arm allows the docking of the target surface by the probe and the vertical slide allows vertical positioning. The accuracy of these roundness measurement machines relies mainly on the rotation quality of the spindle. The measured raw datasets contain the form errors (roundness deviations) of the cylindrical part, error motions of the spindle, linearity and sensitivity of the probe, mechanical behaviour of the measurement machine, and environmental perturbations  [1] [2] [3].
Repeating measurements in a controlled environment several times is generally recommended in Refs. [17, 33]  to enhance the quality of the recorded signals. For the multiprobe method, the asynchronous and random signal effects were reduced by Fourier transformations. A summary of the strengths and constraints related to each of the above-mentioned ESTs is presented in Table  1. In the following sections, the mathematical formulation and the optimisation of the key parameters of the studied method are described in Sections II and III respectively. Section IV focuses on the validation of the investigated method with simulated datasets. Moreover, the influence of angular shift errors on the measurement uncertainties is evaluated in Section V through Monte Carlo simulations. Finally, the effectiveness of the studied method is substantiated by experimental studies in Section VI.
Optimal number of angular shifts N s For one angular shift (N s = 1), solving Eq. (  26   The evolution of the normalised transfer function amplitude |W * (k)| for each harmonic k between 2 and 15 upr is depicted in Fig. 6 , and in Fig. 7  for the cases of one (N s = 1) and two (N s = 2) angular shifts, respectively. When N s = 2, the maximum of |W * (k)| is obtained for k (k + 1) / 2 optimal angular combinations (φ 1 , φ 2 ). The selected angular shifts should correspond to high values of |W(k)| within the subrange of the harmonics. For N s = 1 and considering a raw measured dataset with harmonics in the range  [2, 15]   Fig. 8b  shows a log-log colour-map representation of several isopotentials corresponding to c ∈ [10%, 100%] where a number of bands can be identified. For a given angular shift, the range of harmonics for which |W * (k)| > 50% can be considered.
Validation on simulated datasets The developed and implemented Fourier-based method is tested on simulated datasets, m s i (θ), combining both artefacts' roundness deviations, p(θ), and repeatable spindle radial error motions, B X (θ). Typically, the simulation parameters are designated for the best reproduction of real measurements on the cylindrical part (Table  2 ). Further Gaussian white noise with an amplitude of 20 nm was added to each simulated dataset m s i (θ) to consider the asynchronous contribution of the spindle (ISO 230-7:2015), the influence of environmental disturbances   (thermal drift, structural vibrations, etc. ), and the electrical noise of the acquisition. The measurements are considered made in angle intervals and not in time intervals, in order to avoid the effects of spindle's speed fluctuations.
Only one angular shift was required (N s = 1), as shown in Fig. 8. N φ 1 is a prime number selected in the range  [25, 36000] , such as HCF(M, N φ 1 ) = 1. The angular shift φ 1 was selected with respect to the optimisation described in Fig. 3. The given optimal angular shift is φ 1 = 22. 21 • , and Table  3  summarises the key parameters of the optimisation. The simulated datasets for the cylindrical part roundness deviations, spindle error motions, asynchronous components, and generated measurements are illustrated in Fig. 9  a-d respectively. Classical multistep (with N s = 23 angular shifts), Donaldson reversal, and advanced Fourierbased methods are applied and the calculated residuals are compared in Fig. 10  and Table  4. Here, the residual is defined as the difference between the simulated datasets m s i (θ) without asynchronous errors and the retuned results.
The next step consists of estimating the PV m and MZ m values, as summarised in Table  6  and Fig. 14. Thus, the sphere has a roundness of approximately 31 nm, whereas the spindle error motions are approximately 60. 5 nm. Furthermore, the standard deviation (STD) is below 3 nm, regardless of the applied LSC or MZC methods. Nonetheless, the MZC method always returns more accurate values than the LSC method. An additional multistep experiment was conducted under similar conditions, such as comparing the obtained results to those returned by the Fourier-based method. N = 23 regular angular shifts were conducted to record N = 24 measurements, m i=1:24 (θ). The multistep experiment was repeated 3 times. All raw measured datasets were filtered through a low-pass Gaussian filter F50 upr and the roundness deviations and spindle radial error motions were then separated by using Eq.
(  6 ) and analysed by calculating the LSC and MZC (Fig. 14 ). The given means and STDs values are illustrated in Table  7. The observed STDs were approximately 3 nm and 9 nm, for the roundness deviations and spindle radial error motions, respectively. These values are higher than the values obtained by the developed Fourier-based method. The difference in returned values is caused by the asynchronous and random errors removed from the measured datasets by Fourier calculations, while the other classical methods (Donaldson reversal and multistep) only average those errors. The obtained results (PV m and MZ m ) validate the robustness and effectiveness of the proposed Fourier-based method that can be conducted with a reasonable number of angular shifts (N s = 2 angular shifts for the Fourier-based method and N s = 23 angular shifts for the multistep method).
Conclusion In this study, an advanced error separation method based on Fourier transform was investigated, and it can be applied with a reduced number of angular shifts of the material cylindrical standards. The developed mathematical theory is detailed and simulations were conducted to analyse the harmonic suppression phenomenon. The key parameters, including the number of angular shifts N, the values of angular shifts φ i , and the weighting coefficients a i , were identified by solving non-convex optimisations. The introduced advanced Fourier-based method was  implemented on simulated (nominal) datasets containing synchronous and asynchronous errors that reflect actual roundness deviations of cylindrical and spherical parts and radial error motions of commercial spindles. The returned results show a sub-nanometre discrepancy below 0.
5 nm between the nominal and reconstructed datasets through Fourier calculation. A comparative study between the proposed Fourier-based method and both classical Donaldson reversal and multistep methods was conducted. The given results are more accurate when applying the Fourier-based method, which validates its effectiveness and robustness because it removes all asynchronous errors, whereas the Donaldson reversal and multistep methods only average those errors. Furthermore, the effect of the angular shift errors was numerically investigated, and the returned roundness deviations and spindle radial error motions were still at the nanometre accuracy for angular errors below 0. 2 •. Experimental studies were conducted using a high-precision roundness measurement machine located inside a cleanroom, where temperature and hygrometry were controlled.
, 2020; Dobusch & Heimstädt, 2019; Leone et al. , 2021). The open science movement emerged in the 1990s, when some academics started to share preprints, software, and datasets with their peers on the Internet 2. In the early days of the open science movement, these reformist ideas mostly found resonance in STEM 3 disciplines. The community of management researchers has been reluctant to adopt new open science practices for quite some time. However, the field's interest in the notion of open science has surged in recent years. On the one hand, management scholars have discovered open science as a new research topic, often linked to broader questions of innovation and knowledge management  (Beck et al. , 2022; Vicente-Saez & Martinez-Fuentes, 2018). On the other hand, open science is increasingly included in research institution guidelines  (Aguinis et al.
For example,  Dobusch and Heimstädt (2019)  argue that management journals should experiment with more open peer review. For example, they argue that the peer review process can be opened by inviting "all members of the wider community" to comment on a manuscript (p. 613). In a similar vein, the process can be opened by allowing "direct reciprocal discussions between authors and reviewers" (p. 613). Both proposals advance an interpretation of openness as an input to the research process. Another type of open science practice that interprets openness as input is citizen science. A growing number of management scholars uses new services and tools for crowd sourcing as a research method. In a recent review,  Aguinis and colleagues (2020)  found that, in management research, the use of Amazon Mechanical Turk (MTurk)-a popular crowdsourcing platform-increased from six papers in 2012 to 133 in 2019.
Data exploration In the spirit of autoethnography, the first author condensed some of his observations in a logbook detailing as much as possible what, when, where, and how he had his experiences. This set of notes constituted a rich body of material sometimes mobilized in social media posts, blog articles, and research manuscripts during his experience and contributing to the experience itself. In the spirit of open science, the numerous collaborative posts, reports, and articles completed by their participants (more than 20 texts for OpenAca and more than 50 for OpenWalk), memos, and notes by the first author, and social media data (all specific events had a hashtag which helped us to find the relevant comments, places, and pictures on Twitter, Facebook or Instagram) especially documented these two autoethnographic vignettes.
Moreover, the Samsung health system (via the first author's mobile phone) captured the movements (walks and use of public transportation) in these open events (often involving walks and outdoor sequences). Table  1  summarizes all these (mostly public) data. Numerous online data were co-produced and used openly for this research. In particular, Framapads, collaborative articles, tweets or social media posts were public data. We refrained from sharing the first author's logbooks, personal notes, and data of Samsung health systems (produced by his smartphone) for privacy reasons. For OpenWalk, collaborative articles were part of the inquiry we wanted to implement. They made visible the larger set of concerns identified by the group (especially local people joining the walk) and illustrated how the walk and collective discussion process provisionally converged around a key set of thematic chapters.
For OpenAca, each student group published an article (on Medium) and contributed to a specific Framapad culminating in a collaborative report about what was said and done. We filmed most fixed sequences at the university, outside it or in public space and made them available online on a specific YouTube channel devoted to the course. We livestreamed some of these sequences. To open the course further, we also live tweeted the process, capturing the resulting set of Tweets at a later date (thanks to annual hashtags). The professor and PhD students involved in the coordination identified each year's topics. We used the concluding discussions from previous cohorts and the emergent problems they identified about work practices to give a first direction to the new open course. Both OpenWalk and OpenAca thus contributed to an important set of public data which aided the experiments themselves (as part of their openness) and helped their analysis in the context of this study.
Geospatial data Steps and movements captured using the Samsung Health app and Google Maps. Steps and movements captured using the Samsung Health app and Google Maps. Source: Created by the authors. To elaborate on our two autoethnographic narratives, we especially focus on the first author's experience notes and the events and collaborative documents in which he was personally involved. Beyond things opened, we conceptualize all documents as traces of an opening process, especially that of the present shared by the people involved in OpenAca and OpenWalk. What is opened is the present, the immediate, shared memory of the walk or the course. Walking, chatting, sharing ideas, and experimenting continuously open and re-open the present (gradually) common to all participants  (Semetsky, 2003).
OpenAca: Opening the practices of teaching new ways of working OpenAca started in 2018 with a first course explicitly ministered to students of a master program in management as an open experimentation and an experimentation with openness. Its slogan was "A course open to all, never ending and contributing to knowledge commons," a "course beyond the walls of the university," for which "all contents co-produced had to be open access. " We made explicit the reference to open science in the presentation of the course. Our idea involved a 21-hour long course comprising an introductory seminar about philosophical and historical perspectives on work transformation. This sequence includes an inaugural lecture re-written each year by the professor (the first author of this paper). We choose one or two philosophers to explore one aspect of work transformation and new managerial practices.
The Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) has adopted the FAIR Guiding Principles. We present the Atlas chapter of Working Group I (WGI) as a test case. We describe the application of the FaIR principles in the atlas, the challenges faced during its implementation, and those that remain for the future. We introduce the open source repository resulting from this process, including coding (e. g. , annotated Jupyter notebooks), data provenance, and some aggregated datasets used in some figures in the Atlas chapter and its interactive companion (the Interactive Atlas), open to scrutiny by the scientific community and the general public. We describe the informal pilot review conducted on this repository to gather recommendations that led to significant improvements.
FAIR data principles  3, 4  aim to facilitate open science by ensuring that the data and code used are findable and accessible and can be reused for reproducibility and for further developments using interoperable infrastructures. Guidance and training were provided to all authors, recommending that FAIR principles were adopted in the preparation of the WGI report. This is still ongoing work and has been successful to varying degrees. All the data underpinning the Summary for Policymakers (SPM) figures is now publicly available  5  , but data, metadata and scripts supporting the Technical Summary and chapter figures and key results are still being assembled and are available only in some cases, such as in the Atlas chapter here described. These activities benefited from the adoption of documentation protocols, open-access computing frameworks (such as R or Python) and software management platforms (such as GitHub), which facilitate the collection of metadata (including data provenance) and code, as well as some post-processed datasets.
Results the atlas repository. The Atlas repository contains the code (including Jupyter notebooks), data provenance and some aggregated datasets underpinning key figures of the Atlas chapter and its interactive companion (the Interactive Atlas). Figure  1  shows a schematic representation describing its structure and highlighting its contents. This repository is maintained on GitHub (https://github. com/IPCC-WG1/Atlas), which is the current de facto standard for code sharing with over 200 million repositories and over 65 million registered users. GitHub provides a collaborative environment for code development, with integrated version control and issue tracking among many other features. The repository is self-documented by Markdown-formatted files exploiting GitHub capabilities to browse folders and link to internal and external resources.
Moreover, GitHub enables long-term archiving of repository snapshots, interoperating with services such as Zenodo (http://zenodo. org). The final release of the Atlas repository, containing data, metadata, code and documentation, is available not only through GitHub, as described next, but also as a Zenodo entry  6  with its own persistent Digital Object Identifier (DOI). Reproducible environment. Full reproducibility and reusability of scientific results requires not only the data and code, but also the whole software environment in which the code was executed. There are several solutions to achieve reproducible execution environments  8. We adopted incremental Reproducible Execution Environment Specifications (REES) to build a reproducible environment for the Atlas repository. First, we provide the software versions used as a Conda (https://docs.
conda. io) environment configuration file and a Docker container configuration file, as well as the resulting Docker image to be readily used. In a local computer, the Conda software and environment manager provides a reliable, multi-platform solution, handling versions and dependencies for most of the software stack. The Docker 9 container configuration file and image extend this by allowing system library dependencies to also be encapsulated. Docker images can be deployed by the user in a local computer, but they also pave the way to deploy the execution environment on cloud computing resources, where virtual machines can be created for particular operating systems running a particular Docker image containing the specific environment used to generate a given scientific result. In addition, the contents of the Atlas repository can be run interactively on a browser through the MyBinder.
org 7 links provided. Binder provides a simple way to compile a Docker image from a wealth of different REES, including Conda configuration files. Moreover, the MyBinder. org initiative provides cloud resources to run interactive notebooks based on Docker images. This provides an execution environment for users to try and modify notebooks, without installing software on their computers. This environment can optionally include additional content from a GitHub repository through the nbgitpuller extension, which in this case is used to retrieve the Atlas repository containing the notebooks and the data they use. This approach ensures practical reproducibility for most of the contents of the Atlas repository. The approach can also be replicated to reuse the data and the execution environment, as illustrated in the reusability example below.
Repository structure. The Atlas repository is structured in folders including the auxiliary products (standard grids, reference regions, etc. ) and intermediate datasets (see Fig. 1 ). Most of the data inputs come from ESGF  10  , which distributes the global and regional climate simulations available from CMIP and the Coordinated Regional Climate Downscaling Experiment (CORDEX), respectively. The first step for findability and accessibility is to build an inventory of all data sources used (described in the data-sources folder). This involves parsing metadata for all datasets for scenario and historical experiments in CMIP5, CMIP6 and CORDEX. The final selection of model simulations takes into account the availability of all required variables and analysis periods, discarding erroneous datasets reported in errata registries (e.
g. in Earth System Documentation, ES-DOC, errata search service) along with other issues found during the subsequent data processing as documented in the data-sources folder of the repository. The final inventory is therefore the result of a semi-automated and iterative process. All issues and decisions made are stored in the data-sources folder in the working spreadsheet files used during this process. The final inventory of data sources used, including their version, is also stored as machine-readable CSV files. Moreover, the repository provides unique pointers to the exact data and metadata considered, either as DOIs  11  , ESGF search URLs or handle. net  12 persistent identifiers. Thus, this folder provides both data provenance information and a machine-readable auxiliary product (the inventory of data sources) to be used in subsequent processing steps.
Another auxiliary product stored in the Atlas repository is a set of reference grids used to bring all data sources to a common spatial resolution. The reference-grids folder contains global grid definitions, regular in longitude-latitude, stored in netCDF files containing also common land-sea masks. Commensurable grids (including land-sea masks) are defined starting at 0. 25 by 0. 25 degrees (used to interpolate ERA5 and observational products) and, by aggregating 2 by 2 grid-cells, grids at 0. 5 (CORDEX), 1 (CMIP6), and 2 (CMIP5) degrees resolution were obtained. In addition to these reference grids and masks, there are also other masks used in the Atlas products. These include mountain range masks and missing data masks for several observational products which provide global gridded data but interpolate data from distant stations in empty cells.
A third auxiliary product available at the Atlas repository is the specifications of the new set of AR6 reference regions  13. This is version 4 of the IPCC WGI reference regions and it builds on the previous version used in AR5  14  with slight modifications to split the most climatically heterogeneous regions, and with the addition of 16 new oceanic regions. The polygons defining the regions are provided in the reference-regions folder as CSV files containing corner coordinates and also as shapefile, GeoJSON and R data files. Other sets of regions used in the Atlas are also provided. Namely, IPCC WGII continental regions, 6 land regions subject to monsoons, 28 major river basins, 9 small island regions and another set focused on the analysis of ocean biomes. The Interactive Atlas Dataset (IAD) consists of a set of 25 climate variables and derived indices used in the Interactive Atlas  15  computed over common grids from several observational datasets plus CMIP5, CMIP6 and CORDEX historical and future projections (under different scenarios) aggregated at a monthly temporal resolution.
This dataset will be stored by the IPCC Data Distribution Center (IPCC-DDC; https://ipcc-data. org) for long-term archival and is not available as part of the Atlas repository. However, the repository provides the scripts used for the preparation of the IAD (datasets-interactive-atlas folder), retrieving the data sources from ESGF, computing derived indices, post-processing (including bias adjustment when necessary) and, finally, interpolating each dataset to its reference grid. These scripts rely on the climate4R framework  16  , version 2. 5. 3, an open R framework for climate data access and processing. Only interpolation was delegated to the Climate Data Operators (CDO  17  ), which provides efficient, well-tested, first-order conservative remapping routines, commonly used in climate science.