dataesr/scientific-paragraphs-categorization huggingface dataset:
Data extraction This article does not aim at comparing the devices proposed in the different articles to one another. Such a comparison would not be possible currently due to the diverse assessment methods of the different devices presented in the articles included in this systematic review. Our aim is to summarize the outcomes and results from the literature to guide future developments. To do so, based on the literature, LP extracted information related to three main characteristics presented in the articles (GM verified the accuracy of the data extraction). First of all, we extracted information pertaining to the aim, results and potential bias of the experiments. All the articles were first read to extract the reported sources of bias, e. g. , navigated routes of different difficulties.
Based on the literature, ITS and more specifically learning companions need to adapt to the users  [93]. Biophysiological and behavioral data from the users could be used to adapt the behavior of the learning companion. Developing a learning companion in AR would be beneficial. Indeed, the numerous sensors present in AR headsets, e. g. , head tracking, eye tracking, depth sensors and cameras, could provide highly relevant information regarding the user and the environment to the ITS. In return, the ITS could adapt the information provided to the user (see Figure  6 ). Such adaptation could rely on the research led in pervasive and context-aware AR (see the comprehensive review on the matter from Grubert et al. [96] ). However, the accuracy in the detection of the state of a person based on physiological and behavioral measures remains a challenge.
Such information is important to report as it could contribute to the development of a first model to adapt the navigation advice and would enable to compare the results of the different articles. Our review also presents its own limitations. The keywords used for our search in the Scopus and PubMed databases could have led to the omission of relevant articles. The study of the titles and abstracts from the articles that were included in the review based on outer sources (i. e. , relevant reviews of the field or articles found in our databases search) provides more information on the matter. Indeed,  [30]  and  [31]  were not found in our database searches because the keyword "mild cognitive impairment" (used along the keywords "Alzheimer" and "dementia") was too restricting and should have been replaced by "cognitive impairment".
Also, even if we did include many nouns that could be used to describe a navigation device, i. e. , "device OR tool OR system OR instrument OR glasses OR smartphone OR gps OR virtual reality OR augmented reality OR mixed reality OR windshield", the keywords "rollator" and/or "walker" should have been added as evidenced by the absence of  [21]  in our research. The omission of  [8]  by the databases search was due to the fact that it did not include any keyword in the title or abstract indicating that the device aimed at helping people navigate (nor any related keywords) which made it difficult to find through a database search. Finally, the article  [35]  was not referenced in the Scopus or PUBMED databases. Based on the authors' experience working either with AR/VR and/or medical applications and on the fact that 46 articles were retrieved and read in precaution following our reading of the relevant reviews of the field or articles found in our databases searches, we are confident that the vast majority of the relevant articles corresponding to our topic were included in this review.
It should be noted that petrology (i. e. , the study of rock evolution) is coupled with petrographic analysis, which aims to describe the composition and structure of silicites, allowing for the distinction of genetic types. All observations carried out using exoscopy at low magnification (50x to 200x), with the sample under a slice of water, were recorded in a data table, which was then synthesized into a summary table. This table lists the featured elements (authigenic, non-organic, and organic), as well as inherited structures from the protolith (thus pre-genetic), during siliceous diagenesis, and during different moments of alteration (thus post-genetic). This very detailed description is necessary for identification of archaeological artifacts and possibility of replication by other archaeologists.
Acknowledgments Our team want to thank  Sebastiaan Knippenberg  for his pioneering work and all the information and samples he accepted to share with us. This work was funded by the  French Ministry of Culture (DAC Guadeloupe) , and the  Guadeloupe Régional Council. This study received financial support from the  French government  in the framework of the  University of Bordeaux 's  IdEx "Investments for the Future" program / GPR "Human Past ". We thank the  TraceoLab of Lièges University  for providing us the equipment for microphotography of the silicites.
Within the project frame, the design, implementation, and use of data collected through this protocol is organized in three phases (Fig 1 ): The preparation phase (June 2018-December 2019), the data collection phase (January 2020-December 2022), and the data analysis phase (June 2022-June 2023). The estimated time to complete data collection is two person/months, but the overall period of data collection is longer to accommodate different partners' needs. Due to calendar adjustments derived from the COVID-19 pandemic, data collection and data curation overlapped. The analysis of global data will start once all datasets are curated (December 2022).
Partners' training. To minimize interviewer and coder biases during the application of the protocol, all partners participated in a training workshop. Originally, we conducted three one-week face-to-face workshops during 2019 in Barcelona with 48 partners (S1 File). In March 2021, we conducted one additional two-day online workshop to train a set of 10 new Original map from the Natural Earth data set in the public domain (available from https://www. naturalearthdata. com), elaborated with the R libraries maptools  [23]  and sp  [24]. https://doi. org/10. 1371/journal. pone. 0279847. g002 partners to substitute partners who had to abandon the project because of the COVID-19 pandemic. During the workshops, partners were exposed to the rationale of the project and received detailed explanations concerning the application of all the instruments of data collection.
Villages with more than 500 households should be broken into smaller units and sample one or a few of them. Step 1. In Step 1, partners collect secondary and primary background information from different sources and using different sampling strategies. Background information to be obtained includes general information (e. g. , historical events, protected areas limits) and meteorological data. Background information could be obtained before conducting fieldwork from secondary sources (e. g. , literature review, public records, etc. ), or while in the field through participant observations and conversation with local officials/knowledgeable individuals. Partners should also obtain geo-referenced data on the location of 1) the study site, villages, neighboring protected areas, and officially recognized Indigenous territories; 2) the closest weather station, airport, and/or harbor/port; and 3) the closest market town and administrative center.
Data analysis To test hypotheses on spatial patterns, we will rely on site-specific lists of LICCI and geographical information. We will elaborate a map displaying all LICCI in the inventory and use opensource platforms to visualize the geo-referenced database of reported impacts and use spatial matching techniques to search for patterns across different i) climate-affected areas  [29]  (H1a) and ii) Ko ¨ppen climatic areas  [17]  (H1b). To test hypotheses on socioeconomic patterns, we will use survey data. We will aggregate responses to survey questions to create three dependent (i. e. , number of indicators perceived, number of impactful indicators perceived, severity of impacts) and two explanatory variables (i. e. , direct dependence on natural resources and vulnerability) to be used in multivariate regressions.
The number of indicators and impactful indicators perceived correspond to the sum of LICCI from those included in our survey instrument reported by the interviewed person. The score of perceived severity will be a composite measure created from data on the perceived severity of the various LICCI included in the survey. The number of pebbles allocated to different livelihood activities will be used as a measure of the importance of that activity to the respondent and the number of pebbles allocated to natural resource-related activities will be used as a measure of household dependence on natural resources. We will create an index of household vulnerability by normalizing the measures of the different indicators of household's relative access to the five asset types defined and aggregating them into a single measure.
Data management Partners submit data through a web application specifically developed for this study protocol and accessible for registered partners (S1 File). The application stores data in the browser of the device used, which can then be submitted to a particular website following a set of guidelines (S1 File). To strengthen intercoder reliability and minimize data coding and submission errors, during the data collection period (2020-2022), authors closely worked with partners to clarify doubts in data collection, coding, and submission. The LICCI project participates in the Horizon 2020 Open Research Data pilot and follows the 'FAIR data principles', for which it will make the project's research data findable, accessible, interoperable, and re-usable. Procedures for the management of data, from collection to use after the project ends are outlined in the project's Data Management Plan (DMP), which includes data and metadata standards for use of data, policies for access and sharing, policies for re-use and distribution, and plans for data archiving and preservation.
Data collected with this protocol will only be made open if study participants agree on it. Results from Step 1 of the project will be made available only in aggregated form. Anonymized survey data will be made available with the publication of research results, also in an aggregated format. All data will be stored on and available from Harvard's Dataverse. To describe the underlying data, metadata with sufficient detail will be created to be intelligible for other users. The LICCI metadata will follow a generalized scheme in the Dataverse including, among others, title, creator(s) and contact person(s); date; version; location; contributor, e. g. , funding body, including the grant agreement number; data format(s); keywords; identifiers (DOI and url); access rights (license(s)), and other labels, including labels on the particularities for access and use of cultural heritage data that is digitally circulating outside community contexts to respect local data sovereignty  [31].
Several partners modified the protocol to validate the consensual nature of indicators collected in semi-structured interviews through additional interviews to other informants. Given the large carbon impact of our training strategy  [38] , we have created a number of written and online training materials, as well as a Massive Open Online Course (MOOC) about climate change and Indigenous peoples and local communities (S1 File). We recommend the use of these online materials to guide and train researchers aiming to use this protocol in the future. The use of the online training materials will continue to ensure comparability across datasets, while minimizing carbon impact. The main limitation of this research relates to the ability to discern whether reported changes in elements of the atmospheric, physical, and life systems can be really attributed to climate change, as complexity in such systems and confounding drivers of change (e.
This work is funded by the  European Research Council (ERC)  under grant agreement No  771056-LICCI-ERC-2017-COG. This work contributes to the  ICTA-UAB "Marı ´a de Maeztu" Programme for Units of Excellence  funded by the Expected results and livelihood activities. local climate change impacts research and can provide tangible outcomes for local people who will be able to better reflect on how climate change impacts them. Spanish Ministry of Science, Innovation and Universities  ( CEX2019-000940-M ).
This article, therefore, resonates with the literature on humanitarian action and refugees in Jordan showing how practices of humanitarian organizations and the Jordanian government's encampment policy  (Achilli 2015)  participate in the disempowerment  (Turner 2021 ) and control of refugees  (Lenner 2020). To analyze the evidence produced in this case, we draw on two types of data: a quantitative database with 150 variables coded on 234 documents published by humanitarian actors and IOs between 2012 and 2017; and interviews with experts from IOs and non-governmental organizations (NGOs). Our article offers three main contributions. First, we contribute to the literature on migration-related knowledge production by IOs and its entanglement with migration governance by providing an empirical analysis of an under-researched yet significant form of knowledge, namely evidence, involved in decision-making processes regarding refugee aid in crisis regions.
This shift has been fueled by Jordan's growing concerns over its capacity to manage a protracted crisis and pressure from the EU to contain migrants in the Middle East  (Tsourapas 2019; Ali 2021 ). As a result, humanitarian funding has largely been allocated to resilience projects though with mixed results on refugees' socio-economic empowerment  (Burlin 2020 ). To answer our research questions, we collected data on the major platforms that disseminate information and evidence about the regions where humanitarian work is deployed, focusing on four platforms that contain the most documents published online about refugees and vulnerable populations in the world: 7 the REACH Initiative Resource Centre (130), the UNHCR Data Portal  7 Internal documents which are not publicly disclosed are not considered in the sample.
To explore the relevance of evidence, we look at aspects indispensable for effective and efficient aid delivery  (Mazurana Benelli and Walker 2013)  such as the sectors addressed in the reports, the geographical dispersion of the data, and the disaggregation of results by gender and age. To grasp the process of evidence production and practices of different actors, we also conducted interviews with six experts who worked for international humanitarian organizations: UN agencies (Interviews 1 and 2) and NGOs, two specialized in the production of evidence (Interviews 3, 4 and 5), and one involved in humanitarian service delivery (Interview 6). Interviews focused on cooperation between organizations, processes in data collection, and production of reports, as well as their use of evidence and its general impact for the sector and refugees.
Variability in the appropriateness of evidence The results derived from the MCA indicate that the reports' appropriateness was structured around a first "data and triangulation axis" (horizontal) (i. e. , type of data and use of references) and a second axis understood as a transparency and validation axis (variance in the provision of information on methodology and references) (see Online Appendix   13 We performed an analysis of the evolution of the loss of inertia between different partitions and used indices of validity computed with the R-package NbClust  (Charrad et al. 2014). with standard presentation (Figure  3 ) and little interpretation of results. The number of factsheets also explains why the number of references used in this cluster was low (4 on average). In this cluster, we also learn that a toolkit provided by a Web platform called "Raosoft" 14 was frequently used by humanitarian organizations as a standard of quality and robustness to determine sample sizes according to the base population.
" 16 While 29 percent of registered Syrian refugees in Jordan live in the Azraq camp or the city of Amman, those locations did not attract so much attention in the reports compared with Zaatari. Only 14 percent of documents dealt with Amman and 13 percent with Azraq. Other camps, such as Irbid or Mafraq, attracted much less attention, and it was even worse for out-of-camp populations living in rural or urban informal settlements. Overall, it seems that evidence displayed by the UNHCR-REACH collaboration (Cluster 2) had low relevance for a majority of Syrian refugees in Jordan living outside camps with needs specific to their situation. 16 In other crisis contexts, research also seems to neglect self-settled refugees by focusing on refugees living in camps  (Bakewell 2008). In our academic papers database, only 11 percent addressed Zaatari, a low share that seems to contradict the interviewee's statement.
, Hebrew University, Jerusalem, 1997)  Nevertheless, the story was undoubtedly very popular among medieval and early modern Jews, certainly also reflecting a widely shared view of Christianity, by contrast, as a deceitful religion. As a Jewish story on Jesus and the origins of Christianity, Toledot Yeshu in fact provided them with a corrective to the Christian story, a 'counter-history,' which also allowed them to contest the dominant Christian narrative and uphold their distinct identity in a dominantly Christian world. 4 he scholarly treatment of Toledot Yeshu has often been devoted chiefly to questions of textual history. Such questions are doubtless fundamental, but they sometimes come at the cost of broader historical questions. The texts and manuscripts that have come down to us, as well as the rich body of sources reflective of the circulation and uses of the Jewish Jesus story, do more than just bear witness to a history of textual transmission.
REMERCIEMENTS Le projet CATAPULT, dont certaines données sont analysées dans cet article, a été cofinancé par le programme ERASMUS+ de l'Union Européenne sous la référence 2018-1-FR01-KA204-048053. L'auteur de cet article, également coordonnateur du projet, remercie l'ensemble des membres du consortium pour le travail fourni au cours des trois années du projet… et au-delà.
| Participants Data collection was carried out in the framework of projects 1 dealing with the difficulties and needs of students with dyslexia in higher education in France, and more specifically the difficulties in written text production. The research protocol is divided into three steps: first, a questionnaire on students' activities at university level is elicited; second, a speech and neuropsychological assessment is administered; and third, a psycholinguistic task (text production) is completed by the participants. In order to be able to differentiate between what was a difficulty common to the majority of students and what was more specific to students with dyslexia, an extensive questionnaire was elaborated and all the students in the University of Lyon were invited to complete it.
A total of 1472 students answered this questionnaire. Among them, 83 students with dyslexia and 83 control students matched in gender, age and level of study were selected for the present study. Details about participants are reported in Table  1. Among the 83 students with dyslexia and the 83 control students, approximately 30 students with dyslexia and 30 control students-all monolingual native French-speakers-matched in age, gender and education level agreed to continue the study by completing the speech and language and neuropsychological assessments (step 2) by participating in the text production task (step3). The textual data presented in this article were collected from 21 students with dyslexia and 22 control students (Table  2 ). The texts written by nine students with dyslexia and eight control students were eliminated due to technical problems.
Protocol After the speech and neuropsychological assessments, the students carried out the psycholinguistic task, during which they were asked to produce four texts. Participants were asked to write by hand with pen and paper, as they usually do in university settings, without any time limit, with no specific instructions about revision or spelling so as to collect the most naturalistic data possible. Data collection was conducted during two sessions with a 1-week-long interval between them in order to avoid the effects of fatigue. Each subject had two appointments. During the first week, the project was presented rapidly to the participants who then watched a video presenting the theme for their text production (conflicts between people). Next, they had to produce a narrative or an expository text in written and spoken modalities.
| Data exploitation Spoken data were collected using an audio recorder and a video camera. They were then digitized and transcribed. Written data were collected using digitizing tablets via the Eye and Pen© software  (Chesnet & Alamargot, 2005). Spoken and written data were transcribed according to CHILDES (http://childes. psy. cmu. edu/) conventions with Transcriber for oral data and in Eye and Pen© for handwritten data and exported into the CLAN software, to enable similar coding of spoken and written productions. The texts were segmented into clauses-the clause being defined as a unit of meaning made up of a finite or non-finite verb and arguments-and terminal units (TU)-a unit made up of a main clause and all its dependent clauses. These two types of units have been shown to be appropriate for the evaluation of syntactic development  (Berman, 1998; Hunt, 1970).
| Revision coding After the transcriptions, all students' revisions were coded in the Eye and Pen© software and data were transferred to CLAN to facilitate analysis. All movements involving backtracking (excluding accents or dots on the "i", "j" or bars of the "t") were considered as revisions. Each revision was coded according to three parameters: (1) the place in the text where the revision began (from where the pen was lifted to proceed to the revision); (2) the unit on which the revision was made; and (3) finally the revision type and content (linguistic units involved). These three parameters were linked by an index: the revision number. With regard to the revision type and content, three information items were coded: (a) the distance between the place in the text where the revision began and the unit affected by the revision, which allows to differentiate between revisions made during the writing of the text (and may be more local) and those written after having written the whole text (and may be more global).
ACKNOWLEDGMENTS The authors are grateful to The  ASLAN  project ( ANR-10-LABX-0081 ) of the  Université de Lyon , for its financial support within the  French program  "Investments for the Future" operated by the  National Research Agency (ANR) ; The financial support device PEPS  CNRS  ( Université de Lyon & CNRS ); The  « Ecole Normale Supérieure » from Lyon  for its financial support within the program « projets émergents »; The students for their participation in this study; All the collaborators since the beginning of these projects about dyslexia at University:  Agnès Witko  for her expertise in research and speech therapy;  Raphaëlle Abadie  for her expertise as a neuropsychologist;  Nathalie Bedoin  for her expertise in cognitive psychology;  Louis Maritaud  for his meticulous data coding;  Céline Faure  ( MSH ) for her statistical advice;  Cathy Cohen  and  Harriet Jisa  for their proofreading.