dataesr/scientific-paragraphs-categorization huggingface dataset:
e. 's (from block jackknife) either side of the data point. Data points that are significantly different from zero are shown in grey. The data point representing the topology in a, among a set of three possible topologies, is shown with a black outline. (c) Principal Component Analysis of B10,000 genome-wide nuclear sites (ancient wisent not included due to the sensitivity of PCA to missing data, see Supplementary Fig. 10). (d) Proportion of steppe bison and aurochs ancestry in both wisent and CladeX lineages, calculated with f 4 ratios.
Numerous pulses were found, mostly of Indian origin (Vigna radiata, Vigna mungo, Macrotyloma uniflorum). The rice bean (Vigna cf. umbellata) of Southeast Asian origin was identified at KSK and PKT for the first time in an archaeological context. Another Southeast Asian domesticate, the pomelo (Citrus cf. maxima) was also identified for the first time, at both sites, providing evidence for arboriculture. Some evidence of 'cash' crops or traded plant products included cotton (Gossypium cf. arboreum) and sesame (Sesamum indicum), neither of which are native to southern Thailand. At both sites, a large component of the dataset came from wild/weed species. Often weed flora is used by archaeobotanists to define systems of land use and cultivation practices (e. g. Bogaard et al. 1999; Fuller & Qin 2009).
Acknowledgements Research by Castillo and Fuller on the rice and rice weeds of these sites is supported by a grant from  NERC (UK)  on 'The impact of evolving of rice systems from China to  Southeast Asia ' [ NE/K003402/1 ]. PhD research by Castillo was supported by the  AHRC. Excavations of KSK and PKT were directed by Bellina and supported by the  CNRS  and the  French Ministry of Foreign Affairs. We would also like to thank  Katsunori Tanaka  ( Hirosaki University ) for the aDNA work done on rice from KSK and PKT.
Methods and analysis: The HandiVIH project aims to combine quantitative and qualitative data. The quantitative component is a cross-sectional survey with a control group conducted in Yaoundé (Cameroon). A two-phase random sampling is used (1) to screen people with disabilities from the general population using the Washington Group questionnaire and, (2) to create a matched control group. An HIV test is proposed to each study participant. Additionally, a questionnaire including a life-event interview is used to collect data on respondents' life-course history of social isolation, employment, sexual partnership, HIV risk factors and fertility. Before the cross-sectional survey, a qualitative exploratory study was implemented to identify challenges in conducting the survey and possible solutions.
In the second substudy, members of the DPO mapped during the exploratory work are randomly recruited and offered to participate in the interviewing and to get an HIV testing/counselling after informed consent. Using the same statistical method as for the cross-sectional components, the characteristics of this subgroup will be compared with those of the participants in the main study to better understand to what extent data obtained from DPO members may reflect the situation of the overall population of people with disabilities. For these two substudies, no formal sample size calculation has been performed because of their exploratory nature. However, a sample size of at least 50 participants in each sub-study was targeted in order to provide a power of 80% and to obtain results with a precision of at least 15%.
DISCUSSION To the best of our knowledge, this study will be one of the most comprehensive surveys on HIV and SRH to be conducted among people with disabilities in Sub-Saharan Africa. It will use a rigorous methodology to provide quantitative data on the burden of HIV among people with disabilities as well as information on their life situation. In the cross-sectional component, the study attempts to overcome several methodological difficulties in identifying persons with disabilities that deserve attention. First, a relatively complex sampling design has been chosen to overcome the problem of identifying people with disabilities in the absence of a sampling frame, using a two-phase cluster random sampling with screening of disability at phase one. The rationale for this design is to use a first simple screening tool (here the Washington Group short set+2 questions) to reduce the population in which the more complex 'diagnosis' tool (here the Washington Group extended set) is used.
In this study, it was decided to include two additional questions to the Washington Group short set to improve its sensitivity to detect intellectual or mental impairment because it was assumed that people with these impairments may be at an increased risk of sexual abuse and violence. The main potential limitation of this two-phase design is the inability of the screening tool (Washington Group questionnaire) to correctly partition the population into two groups defined by the disability status. Various tools have been used to identify people with disabilities in the surveys and comprehensive discussions of their limitations have already been published. 13 26 34 68 n this study, the two important features sought for the tool used to measure disability were its coherence with the ICF disability model and its ability to provide valid and reliable data that could be compared with similar data from other countries.
Acknowledgments This research was supported by grant  ANR 11-FRQU-004-01  and by the  CNRS Défi   S2C3 2016  grant for the project  IM3CP. Thanks are due to  Mickael Berthon  for the computer programming and to  Danae Farges ,  Cedric Barbosa , and  Marie Valette  for their help with data gathering and formatting.
Approval for the indication of GH treatment of short stature due to SHOX deficiency was based on data from the 2-year randomised treatment phase of a single clinical trial  [17]. After completion of this randomised phase, all participants were offered GH therapy until attainment of near-adult (final) height  [16]. It is important to determine whether results from clinical trials are matched by subsequent outcomes in routine clinical practice. Observational programmes, such as the Genetics and Neuroendocrinology of Short Stature International Study (GeNeSIS), are carried out to assess safety and effectiveness outcomes of children with growth disorders, with or without GH treatment. The present study aimed to analyse GeNeSIS data for patients with short stature associated with SHOX deficiency and to evaluate long-term effects of GH therapy on safety and near-adult height.
Patient Populations GeNeSIS (ClinicalTrials. gov: NCT 01088412) was a prospective multinational, open-label, paediatric surveillance programme designed to examine the long-term safety and efficacy of GH (Humatrope ® , Eli Lilly and Company, Indianapolis, IN, USA) administered for treatment of short stature. Patients were enrolled from March 1999 to September 2013. Among the causes of short stature, the database includes paediatric patients who have received GH therapy for short stature associated with SHOX deficiency. SHOX deficiency was diagnosed by investigators on the basis of clinical signs of LWS and/or molecular genetic data available at the time of presentation or study enrolment. Patients enrolled in GeNeSIS and diagnosed by investigators as having Turner syndrome were not included in the present analysis.
Both the GeNeSIS observational study and the clinical trial included patients who were followed until they achieved near-adult (final) height. It was possible for patients in the clinical trial to subsequently be enrolled in GeNeSIS; therefore, it was ascertained that such patients were excluded from analysis within the GeNeSIS cohort and only included in the clinical trial cohort for safety assessments and analysis of patients who achieved near-adult height. Patients who had entered puberty at GH initiation were not excluded from GeNeSIS participation, whereas all patients in the clinical trial were prepubertal when starting GH. Therefore, a subgroup of patients in GeNeSIS who were prepubertal at the time of GH initiation and who had near-adult height data available was also assessed. The clinical trial protocol was approved by all appropriate local ethics review committees and the GeNeSIS protocol adhered to the applicable regulatory requirements in the participating countries, with appropriate institutional review board approvals.
Study Evaluations Baseline data collected at the entry to GeNeSIS included medical history, physical examination, laboratory values and pubertal status, as provided by the attending physician. Baseline data in the clinical trial included medical history, height, weight, parental heights and bone age. All patients had SHOX deficiency confirmed by centralised genetic analysis of the SHOX gene  [8]. Investigators also reported the clinical phenotype, with categorisation as either having LWS or non-syndromic short stature. At the start of GH therapy, all patients were prepubertal (Tanner stage 1), had no evidence of GH deficiency or resistance and were not taking any growth-influencing medications. Height, weight and pubertal development changes were evaluated at follow-up visits. Patients from GeNeSIS and the clinical trial were considered to have reached near-adult height (final height) during follow-up if they attained one of the following criteria: height velocity <2 cm/ year, X-ray of the hand showing closed epiphyses or bone age >14 years for girls or >16 years for boys.
Bone age was assessed from radiographs of the left hand and wrist, which were read using Greulich and Pyle standards  [20]. The clinical trial predominantly enrolled patients from central European countries; therefore, standard deviation scores (SDS) for height were calculated for both GeNeSIS and the clinical trial using data from a central European reference population  [21]. Nearadult height was expressed as height SDS for chronological age at the time of the measurement, including when adult height was considered as attained, which could potentially increase the observed effect of treatment but is a well-accepted method for SDS calculation. Body mass index SDS was determined from European reference data  [22]. Safety analysis for inclusion in this report was based on adverse events reported for patients who received GH therapy.
Statistics Data for patients with SHOX deficiency in GeNeSIS were analysed using descriptive statistics. Results for continuous variables are presented as means ± SD with 95% confidence intervals (CIs). Information on categorical variables is presented as number of patients and percentage of the relevant total population. Safety data were assessed for all patients who received GH treatment in both GeNeSIS and the clinical trial. Near-adult heights were assessed using mean and 95% CI of height SDS for age at the time of measurement.
Baseline Data for Patients with SHOX Deficiency in GeNeSIS At the March 2014 data lock for this report, the GeNeSIS database contained evaluable information for 21,577 GH-treated paediatric patients, including 521 patients (314 female, 207 male) with a diagnosis of SHOX deficiency enrolled between 2000 and 2013. The majority of the GH-treated SHOX-deficient patients were from Germany ( n = 197) and France ( n = 180), followed by the USA (n = 61), Spain ( n = 25) and Czech Republic ( n = 20), with the remainder spread among 11 other countries. Among the 521 patients, the numbers with an investigator-provided diagnosis of either LWS (56%) or nonsyndromic short stature (44%) are shown in Figure  1  , together with available information on identified gene defects. Molecular alterations affecting the SHOX gene, as described by the investigator, were reported for 207 (71%) of the 292 patients with a diagnosis of LWS.
Near-Adult Height Data Near-adult height data were available at the time of analysis for 90 GH-treated patients with SHOX deficiency in GeNeSIS, 42 of whom were prepubertal at baseline; near-adult height data were available for 28 patients in the clinical trial, all of whom were prepubertal at baseline. The genotype and phenotype data for these patients are shown in Table  3. In both GeNeSIS and the clinical trial, the majority of patients with available near-adult height data had a diagnosis of LWS. For patients in GeNeSIS with genetic data available, the proportions with an identified mutation, deletion or duplication were very similar to the proportions identified during screening for the clinical trial ( Table  3  ). Patient characteristics, auxological parameters and GH treatment details at GH initiation and near-adult height are summarised in Table  4.
Discussion Among patients enrolled in the GeNeSIS observational study and treated with GH in routine clinical practice, a diagnosis of SHOX deficiency was reported by physicians for 521 patients. For 56% of these patients the diagnosis was reported as LWS, and for 44% the phenotype was reported to be "non-syndromic" SHOX deficiency (also known as "idiopathic" short stature). This phenotype distribution was similar to the approximately equal proportions of LWS versus idiopathic short stature for the total cohort included in the clinical trial  [17]. There was also 1 GH-treated patient in GeNeSIS with a diagnosis of Langer mesomelic dysplasia, the homozygous form of SHOX deficiency; although GH treatment may have limited effectiveness in promoting height gain in patients with this condition, the patient was included in the analysis in reflection of the real-world nature of data from an observational study.
Acknowledgements Both GeNeSIS  and the clinical trial were sponsored by  Eli Lilly and Company. The authors are grateful to  Valérie Cormier  ( Inserm U781, Paris, France ) for assistance with interpretation of genetic alterations. Medical writing assistance was provided by  Peter Bates  ( CMWS, UK ) and  Caroline Spencer  ( Rx Communications, UK ) funded by  Eli Lilly and Company. The authors thank all of the investigators who participated in the two studies and all of the patients and their families.
1 F. Dietrich, Paris School of Economics (CNRS); C. List, LSE; R. Bradley, LSE. We have presented this paper at several seminars and conferences, and we thank the audiences for helpful comments. These occasions include: D-TEA 2010 (HEC & Polytechnique, Paris, June 2010), LSEís Choice Group Seminar (LSE, September 2010), Pluralism in the Foundations of Statistics (University of Kent, September 2010), and Decisions, Games, and Logic 2012 (University of Munich, June 2012). Although this paper is jointly authored, List and Bradley wish to note that the bulk of the mathematical credit should go to Dietrich. Dietrich was supported by a Ludwig Lachmann Fellowship at the LSE and the French Agence Nationale de la Recherche (ANR-12-INEG-0006-01). List was supported by a Leverhulme Major Research Fellowship and the Franco-Swedish Program in Philosophy and Economics.
Because of the high heritability of non-metric variations  [16, 31] , these phenotypic data are studied in order to assess the social structure of necropolises  [31, 44, [47] [48] [49]. In particular, teeth are often singled out for their potential to identify biological relatives  [50] [51] [52]  and even siblings  [15]. More recently, advances in paleogenetics allow to compare cemetery organization and kinship from ancient DNA analysis, also with some precise genetic affiliation  [53] [54] [55] [56]. Affinities obtained from these two methods-non-metric and genetic-are correlated  [57] [58] [59]. Paleogenetic analyses are destructive and dependent on the preservation of the remains-ancient DNA may not be conserved. So far, external morphometric analyses of the crown are used to assess biological affinities, providing information that describes in essence the macrostructural outcomes of dental development.
Microtomographic record The UM2 were scanned on Skyscan 1076 X-ray equipment set at the MRI platform (University Montpellier 2, France). Acquisitions were realized according to the following parameters: 100 kV voltage, 100 μA current, a 1. 0 mm aluminum filter and a rotation step each 0. 20°. The software Nrecon v1. 6. 6 (Skyscan) was used to reconstruct the final volumes with an isotropic voxel size ranging from 17. 93 μm for isolated teeth to 36. 18 μm for jaw fragments. Following the half-maximum height method  [130, 131] , a semi-automatic threshold-based segmentation with manual corrections was conducted using Avizo v. 7 (VSG)  [62, [84] [85] [86] [87] 89, 94, [132] [133] [134] [135]. Crowns were digitally isolated from roots  [85]  and three-dimensional (3D) surface models were generated using a constrained smoothing algorithm.
Geometric morphometric analysis of EDJ shape Using the software Viewbox 4 (dHAL software, Kifissia, Greece), a 3D template of 114 points was created with an assemblage of three sets of 3D landmarks (S5 Fig). Compared to studies aiming to assess variations at a macroevolutionary scale  [91, 95] , a large number of landmarks and semilandmarks was placed in order to finely quantify morphological EDJ variations in a microevolutionary context. The first set includes five anatomical landmark points: four were digitized on the tip of the dentin horn of corresponding four main cusps (i. e. protocone, paracone, metacone, hypocone) and one on the maximum lower part of the occlusal basin. Although unworn to slightly worn UM2 were selected, four teeth exhibit small dentin patches. Based on morphology observed for preserved dentin horns, reconstructions of the apex of dentin horn tips were made using Avizo v.
Acknowledgments MicroCT data used in this study were produced through the microCT facilities of the  MRI platform and LabEx CeMEB. The authors are grateful to  Renaud Lebrun  ( Université Montpellier 2 ) for his help with microCT acquisitions and  Eline Schotsmans  for her help on the English manuscript. For fruitful discussions about Gurgy, we thank  Léonie Rey ,  Maïté Rivollat  and  Aline Thomas. The authors are also grateful to  Christopher Dean ,  Debbie Guatelli-Steinberg , the  Academic Editor  and the three reviewers for their valuable comments that have greatly improved the paper.
The research was supported by the  Research National Agency  through the  DHP  project (dir:  S. Rottier ;  2012-14 ;  Université Bordeaux 1/ LaScArBx ;  ANR-10-LABX-52 ) and the PEPS 3Dent'in (dir:  P. Bayle ;  2013-14 ;  PEPS IdEx Bordeaux/CNRS ;  ANR-10-IDEX-03-02 ). M. Le Luyer  benefited from a doctoral grant of the  Ministère de l'Enseignement Supérieur et de la Recherche. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Our categorization currently comprises more than 400 subfields or technical specialties (e. g. databases) for about 40 fields of study (e. g. computer science). Our team then used this material in the process of providing lexical entries, for its categorization. This step of the project is particularly important in order to obtain a first lexical corpus rich enough to play on the platform at its release, before any further vocabulary can be collaboratively built. This first version of the platform database will then contain entries submitted by our team, as well as science vocabulary from an online corpus called Lexico-Science (http://lexico. unisciel. fr/) whose owners generously agreed for us to use in our project.
Conclusion Cognitive ergonomics literature has taught us that no matter how innovative a tool is, it only starts to exist when it is used, i. e. to properly analyze a tool (or instrument), one needs to consider it in the context of its actual use  (Rabardel, 1995). As a follow-up research study, we have assumed so far that students will be more involved and thus more motivated: as we said, this is a user-generated content database. Given that the use of the platform is part of the teaching scenario, the students will have to take part in the generation process of the content. This hypothesis will be tested in the near future, once the new version platform is up and running. Following research questions are thus inherent to computer assisted language learning; not whether an invention works but rather in which contexts it works or does not, and how and why (e.
Acknowledgements The present paper is dedicated to the memory of two departed giants in the realm of spatial ecology,  Ilkka Hanski  and  Richard Levins , whose work has been a great source of inspiration for us and many of our colleagues. This work was conducted as a part of the 'Stoichiometry in metaecosystems' working group at the  National Institute for Mathematical and Biological Synthesis , sponsored by the  National Science Foundation , the  U. S. Department of Homeland Security  and the  U. S. Department of Agriculture  through  NSF  Award # EF-0832858 , with additional support from The  University of Tennessee, Knoxville. D. G. was supported by the  NSERC  and the  Canada Research Chair Program. F. M. was supported by the  CNRS  and through the  ANR-funded project   ARSENIC  ( ANR-14-CE02-0012 ).
Participants This research employed a nationally representative probability sample of 813 Hungarians, selected randomly from an Internetenabled panel, including 20,000 members, with the help of the Solid Data Ltd. , in October-November 2014. For the preparation of the sample, a multiple-step, proportionally stratified, probabilistic sampling method was employed. Members of this panel used the Internet at least once a week. The demographic characteristics of the panel are permanently filtered. More specifically, individuals were removed from the panel if they responded too quickly (i. e. , without paying attention to their response) and/or had fake (or not used) e-mail addresses. The sample was nationally representative in terms of gender, age, level of education, and location of residence.
RESULTS Descriptive statistics of the above-mentioned questionnaires with ranges, summed scores, standard deviations, and intercorrelations can be seen in Table  1  (see the Dataset here). Individual differences in terms of Big Five traits and BIDR dimensions were either unrelated to or very weakly related to CAT scores. Only Openness and BIDR-SDE were negatively and weakly related to CAT scores. Finally, CMQ and CAT were highly associated with each other.
There has been much recent interest in the potential opportunities for extracting information contained in large datasets arising through big data initiatives and the many crowdsourcing activities. Much of this interest relates to the high data volumes and low cost of crowdsourced data and to the opportunities for extracting useful and novel knowledge by integrating information from the many data silos under big data. A number of publications have described the potential opportunities arising from analysis of crowdsourced data  [1] [2] [3] [4]  but one of the critical and as yet unaddressed issues is how to deal with conflicting information. Most of the current solutions to this problem adopt a Linus law or majority rules approach, where the majority view of contributors is deemed to be correct.
The term 'crowdsourcing' originally referred to the ability of citizens to validate and correct the errors that an individual might make and to potentially arrive at some truth  [14]. A recent example is the Geo-Wiki project. This web-based interface to Google Earth was initially used to validate a global biofuels availability dataset  [15, 16]  and has subsequently been used for a number of other campaigns. Typically Geo-Wiki campaigns captures data describing the land cover class at a series of locations. In some campaigns additional information is captured for example on the amount of human disturbance in the scene, the user confidence in their class allocation, etc, and, depending on the campaign, the points may be selected at random or they may be repeatedly sampled. Currently many Geo-Wiki analyses apply a geographically weighted averaging approach as described in Comber et al  [4]  to combine crowdsourced land cover data.