dataesr/scientific-paragraphs-categorization huggingface dataset:
In contrast, eastern individuals were better grouped than previously. The sNMF program was used to investigate population clustering of the 323 C. mauritiana individuals in K clusters and to infer individual ancestry coefficients. The K values ranging from 5 to 8 minimized the cross-entropy criteria (CEC) (Fig. S3a ). An overview of the Q matrices (data not shown) and their graphical representations (Fig. S3b, c, d ) led us to select a structure in seven main clusters as the most relevant since K = 7 minimized admixture events while mostly preserving the source population affiliation (Fig. 3b ). The bar plot revealed that clusters of individuals matched their geographic region of origin on the island (north-east, east, west, north-west). Source populations from the south were distributed in two clusters corresponding to south-eastern and south-western regions, respectively.
Acknowledgements We thank the  Conservation Botanique National de Mascarin (CBNM)  for providing records on C. mauritiana distribution and the  METEOR plateform of the Centre de coopération internationale en recherche agronomique pour le développement (CIRAD)  for meteorological data. We also thank  Annette Lashermes  for assistance with GIS data management and CIRAD for hosting visiting researchers at the  Pôle de Protection des Plantes (3 P, Unit PVBMT), Saint-Pierre (La Réunion ). Collection permits for the sampling of C. mauritiana populations in protected areas were granted by  Reunion Island National Park  (sampling permit code:  DIR-I-2015-154 ;  DIR-I-2016-069 ). This work was financially supported by the  European Union  ( European Regional Development Fund) ,  Région Réunion , and the  Institut de Recherche pour le Développement (IRD)  ( CAFEDIV  project: 'Caractérisation et valorisation d'une espèce endémique des forêts réunionnaises: le caféier marron'; GURDTI/.
The EFSA Panel on Contaminants in the Food Chain (CONTAM) established a tolerable daily intake (TDI) for fumonisin B 1 (FB 1 ) of 1. 0 lg/kg body weight (bw) per day based on increased incidence of megalocytic hepatocytes found in a chronic study with mice. The CONTAM Panel considered the limited data available on toxicity and mode of action and structural similarities of FB 2-6 and found it appropriate to include FB 2 , FB 3 and FB 4 in a group TDI with FB 1. Modified forms of FBs are phase I and phase II metabolites formed in fungi, infested plants or farm animals. Modified forms also arise from food or feed processing, and include covalent adducts with matrix constituents. Non-covalently bound forms are not considered as modified forms. Modified forms of FBs identified are hydrolysed FB 1-4 (HFB 1-4 ), partially hydrolysed FB 1-2 (pHFB 1-2 ), N-(carboxymethyl)-FB 1-3 (NCM-FB 1-3 ), N-(1deoxy-D-fructos-1-yl)-FB 1 (NDF-FB 1 ), O-fatty acyl FB 1 , N-fatty acyl FB 1 and N-palmitoyl-HFB 1.
Increased incidence of megalocytic hepatocytes in the liver was established as the critical effect and a BMDL 10 of 0. 1 mg FB 1 /kg bw per day was derived. The CONTAM Panel used the BMDL 10 of 0. 1 mg/kg bw per day and an uncertainty factor (UF) of 100 for intra and interspecies variability to derive a TDI of 1. 0 lg FB 1 /kg bw per day. Based on structural similarity, and the limited data available indicating similar toxic profile and toxic potencies in the same order of magnitude, the CONTAM Panel decided that FB 2 , FB 3 and FB 4 should be included in a group TDI with FB 1. It should be noted that the in vivo toxicology database for FB 2-4 is very limited. Because of the currently insufficient data modified forms of FB 1-4 could not be included in this group TDI. The CONTAM Panel noted that based on the available evidence it can be assumed that modified forms of FB 1-4 exert lower toxicity than their parent compounds.
However, this could not be quantified. Standards and calibrants for FB 2-6 and for modified forms of FBs are needed for analytical and toxicological purposes as well as more information on occurrence of FB 2-6 and of modified FBs in order to prioritise toxicity testing. More information on the in vivo toxicokinetics for modified forms of FBs and also for FB 2-6 is needed together with in vivo toxicity data on FB 2-6 and of any modified FBs using pure compounds and in particular on the toxicity of hydrolysed FBs using pure compounds to assess if toxicity mitigation measures (e. g. nixtamalisation) are effective. Background Terms of Reference as provided by the requestor Following a request from the European Commission, the risks to human and animal health related to modified forms of the Fusarium toxins zearalenone, nivalenol, T-2 and HT-2 toxins and fumonisins were evaluated in the scientific opinion on the risks for human health related to the presence of modified forms of certain mycotoxins in food and feed 1  , adopted by the EFSA Panel on Contaminants in the Food Chain (CONTAM) on 25 November 2014.
Other groups of fumonisins are the A, C and P series, usually representing less than 5% of total fumonisins. These were not further considered as they were not part of the Terms of Reference (see  Sections 4 and 6). The CONTAM Panel reviewed the new relevant data on FB 1-4 (i. e. published after 2011) to evaluate whether the group tolerable daily intake (TDI) established for FB 1-3 by the Scientific Committee for Food  (SCF 2003)  needs to be revised and whether or not FB 4 should be included in the group TDI. In addition, for the modified forms of FB 1-4 identified to date the methods currently available for their analysis were reviewed. In line with the previous EFSA opinion on modified mycotoxins (EFSA CONTAM Panel, 2014), modified forms of fumonisins arising from both plant and fungal metabolism, formed as a consequence of food processing and transfer from feed to animal tissues used as food were considered for possible inclusion in the group health-based guidance values (HBGVs).
Methodology for data collection and study appraisal A pilot search in Web of Science 6  in December 2015 for publications that could potentially be relevant for the present assessment was carried out. From this, it became clear that due to the sheer amount of publications, a review of abstracts and identification of potentially relevant publications could not be done with the resources available at EFSA and the and the EFSA Working Group (WG), and the given deadline for the present mandate. Therefore, a call for a literature search and review was launched in March 2016 within the Framework Contract No OC/EFSA/AMU/2014/01 Lot 2 Chemical/toxicological -FWC 6 with the aim to identify and collect relevant literature related to fumonisins and their modified forms to support preparatory work for the present opinion and that on animal health risk assessment.
The CONTAM Panel concluded that the database was insufficient for including N-fatty acyl FBs in a group with FB 1-4. The information on in vivo and in vitro effects of other modified forms (NCM-FB 1 , NDFB 1 ) indicate a lower toxicity in comparison with FB 1 , but there are insufficient data to make conclusions on their toxicity and in consequence the CONTAM Panel concluded that NCM-FB 1 and NDFB 1 should not be included in a group TDI with FB 1-4.
g. Kim and Chun, 2015a) ; see below for further details. -To reduce data volume, daily mean three-dimensional (3-D) variables are requested for only the eight pressure levels used by CMIP5: 1000, 850, 700, 500, 250, 100, 50, and 10 hPa. These data will be used mainly to examine the QBO influence on other regions of the atmosphere (e. g. on the North Atlantic Oscillation, NAO) and higher vertical resolution is not considered necessary. Horizontal resolution should be the same as the model but if data volume is an issue then a reduced grid is acceptable, provided the reduction method is documented. To examine the daily mean and monthly mean QBO zonal mean momentum budget, terms making up the TEM zonal momentum equation (e. g. Andrews et al. , 1987, pp. 127-130)  are requested following the recipe given by Gerber and Manzini (2016a, Appendix A3), but also see their corrigendum  (Gerber and Manzini, 2016b).
high-and low-top results in Osprey et al. , 2013). However, it is not strictly necessary for a model to display QBO-like variability in the equatorial stratosphere as additional insight can be gained by comparing models with and without this property. Models with QBO-like variability but without a properly resolved stratosphere (e. g. with upper boundary below 1 hPa) are also considered since, again, this potentially provides guidance on the level of stratospheric detail that is required in order to reproduce a QBO. There are 17 models or model versions participating in phase 1 of QBOi (i. e. data from 17 models have been uploaded or are planned for upload to the shared QBOi repository; see the Supplement for details of this repository). These models are listed in Table  5  along with the institutes and investigators using the models and their contact information.
Closing remarks and future plans The QBO is arguably the most conspicuous and regular mode of variability observed anywhere in the atmosphere that is not directly related to either the annual or diurnal cycles. At a fundamental level and for current conditions, it can be considered to be purely an atmospheric dynamical mode of variability, despite possible external influences from variability in the oceans, the solar cycle, or changes in atmospheric composition. Therefore the primary goals of phase 1 of QBOi are achievable using atmosphere-only global models that are computationally relatively inexpensive to run. To date (January 2018) output from 17 models and/or model versions (Table  5 ) has been uploaded or is planned for uploading to the shared database. The goals of phase 1 of QBOi are to compare, for present-day conditions, the accuracy of the morphology of the simulated QBOs across models and relate this to differences between models in the representation of the forcing mechanisms (e.
However, 2002 ozone amounts are likely to be strongly perturbed because of the Southern Hemisphere sudden stratospheric warning (e. g. Shepherd et al. , 2005)  and for ozone a 2-D climatological field representative of the 1990s is preferable. For SSTs and sea ice amounts CMIP5 1988-2007 climatologies are available from http://www-pcmdi. llnl. gov/projects/amip/ AMIP2EXPDSN/BCS/amipbc_dwnld. php. As Experiment 2 is the control for Experiments 3 and 4 (2×CO 2 and 4×CO 2 , respectively) the average CO 2 amount for 2002 should be used as the baseline 1×CO 2 amount. 3 These ozone data are identical to those which previously could be obtained from https://groups. physics. ox. ac. uk/climate/osprey/ QBOi_O3/. Although the use of different length climatologies for different forcings is not ideal and does not provide direct comparison to the 30-year period of Experiment 1, the observed dependence of the QBO on a changing climate through this period appears to be negligible.
A4 Experiment 5 -QBO hindcasts These are atmosphere-only experiments initialized from reanalysis data and providing multiple ensembles of short integrations from a relatively large set of start dates sampling different phases of the QBO. The prescribed start dates (i. e. atmospheric initial conditions) are 1 May and 1 November for the years 1993-2007 (i. e. 15 years with a total 30 start dates). The duration of each hindcast should be at least 6 months but preferably 9-12 months. As with Experiment 1 the boundary conditions and external forcings should be the same as those specified for the CMIP5 AMIP experiment  (Taylor et al. , 2012). CMIP5 inter-annually varying sea ice and SSTs can be obtained from http://www-pcmdi. llnl. gov/projects/ amip/AMIP2EXPDSN/BCS/amipbc_dwnld. php, while the CMIP5 external forcings for radiative trace gas concentrations, aerosols, solar, explosive volcanoes, etc.
, can be obtained from http://cmip-pcmdi. llnl. gov/cmip5/forcing. html# amip. Ozone forcing datasets appropriate for use in hightop models are available from  Osprey et al. (2011) : https: //doi. org/10. 5281/zenodo. 1035142. Initial data for the hindcasts should be taken from the ERA-Interim reanalysis  (Dee et al. , 2011) , which can be downloaded from http://apps. ecmwf. int/datasets. Registration is required; if downloading many start dates from this site, it may be easier to use the "batch access" method described on the site, although interactive download of each date is also possible. Data are available on either standard pressure levels or original model levels and in either grib or netCDF formats. The ensemble is expected to be generated by perturbing the initial conditions by a small anomaly, which requires no more than changing the bit pattern of the simulation.
Acknowledgements. The design of the experiments described here grew out of community discussions at the first QBOi workshop in March 2015 in Victoria,  Canada. Funding for the workshop from the  UK Natural Environment Research Council  ( NE/M005828/1 ), the  World Climate Research Programme (WCRP) ,  Stratospheretroposphere Processes And their Role in Climate (SPARC)  activity, and the  Canadian Centre for Climate Modelling and Analysis  is gratefully acknowledged. We further acknowledge the scientific guidance of the WCRP for helping motivate this work, coordinated under the framework of the  SPARC QBO initiative (QBOi)  led by  James Anstey ,  Neal Butchart ,  Kevin Hamilton , and  Scott Osprey. The Centre for Environmental Data Analysis (CEDA) have very kindly offered to host the QBOi data archive.
Neal Butchart and Adam Scaife were supported by the  Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme  ( GA01101 ). Scott Osprey  and  Lesley Gray  were supported by  NERC  projects  NE/M005828/1  and  NE/P006779/1. Shingo Watanabe  and  Yoshio Kawatani  used the Earth simulator for QBOi simulations and were supported by the  SOUSEI programme, MEXT Japan , and the  Japan Science and Technology Agency (JST)  as part of the  Belmont Forum. Yoshio Kawatani  was supported by  Grant-in-Aid for Scientific Research B (26287117), joint international research  ( 15KK0178 ) from the  Japan Society for the Promotion of Science , and the  Environment Research and Technology Development Fund  ( 2-1503 ) of the  Ministry of the Environment, Japan. Francois Lott  and  Scott Osprey  were supported by the  ANR/JPI-Climate/Belmont Forum  project  GOTHAM  ( ANR-15-JCLI-0004-01 ).
Federico Serva  was supported by the  European Commission  under grant  StratoClim-603557-FP7-ENV. 2013. 6. 1-2 , with computing resources for the ECHAM5sh simulations provided by an  ECMWF  special project. Young-Ha Kim  was supported by the  Basic Science Research Program  through the  National Research Foundation of Korea  funded by the  Ministry of Science, ICT & Future Planning  ( NRF-2015R1C1A1A02036449 ). Holger Pohlmann was supported by the  German Federal Ministry for Education and Research (BMBF)  project  MiKlip  ( FKZ 01LP1519A ) and thanks  Elisa Manzini  for providing additional information on the MPI model. BSC contribution is supported by the  Spanish MINECO -funded  DANAE  project ( CGL2015-68342-R ) and  Red Española de Supercomputación  ( RES  project  AECT-2017-3-0015 ).
Rocky coast erosion (i. e. , cliff retreat) is caused by a complex interaction of various forcings that can be marine, subaerial or due to rock mass properties. From Sunamura's seminal work in 1992, it is known that cliff retreat rates are highly variable over at least four orders of magnitude, from 1 to 10 mm yr -1. While numerous local studies exist and explain erosion processes at specific sites, there is a lack of knowledge at the global scale. In order to quantify and rank the various parameters influencing erosion rates, we compiled existing local studies into a global database called GlobR2C2 (which stands for Global Recession Rates of Coastal Cliffs). This database reports erosion rates from publications, cliff setting and measurement specifications; it is compiled from peer-reviewed articles and national databases.
In order to be homogeneous, marine and climatic forcings were recorded from global models and reanalyses. Currently, GlobR2C2 contains 58 publications that represent 1530 studied cliffs and more than 1680 estimated erosion rate. A statistical analysis was conducted on this database to explore the links between erosion rates and forcings at a global scale. Rock resistance, inferred using the criterion of  Hoek and Brown (1997) , is the strongest signal explaining variation in erosion rate. Median erosion rates are 2. 9 cm yr -1 for hard rocks, 10 cm yr -1 for medium rocks and 23 cm yr -1 for weak rocks. Concerning climate, only the number of frost days (number of day per year below 0 • C) for weak rocks shows a significant, positive, trend with erosion rate. The other climatic and marine forcings do not show any clear or significant relationship with cliff retreat rate.
g. , climate, homogeneous lithology and so on) In order to overcome biases inherent to individual approaches, studies have been conducted at global scale. They are often based on morphometry; for example, the classic study by  Emery and Kuhn (1982)  interprets cliff profile morphology as a function of cliff top and toe composition and marine and subaerial relative process efficiency. The only global, quantitative, dataset was produced by  Sunamura (1992) , and was based on quantitative studies published prior to that date. Sunamura's database was only used by  Woodroffe (2002)  to evaluate ranges of erosion rates for different lithological types. Up until this point, those rates have never been related to environmental factors. Since Sunamura's 1992 compilation, 26 years ago, many new quantitative studies have been published.
g. ,  Dewez et al. , 2013; Earlie et al. , 2015; Gulayev and Buckeridge, 2004; Letortu et al. , 2015; Rosser et al. , 2007; Young and Ashford, 2006). This contemporary high spatial accuracy is then combined with high time resolution (up to 20 min) with the detection of decimetric fragments from cliff faces  (Williams et al. , 2018). Cliff recession phenomena have never been so well defined in space and time. It is now time to sort through the possible processes generating cliff responses. We updated the dataset from  Sunamura (1992)  into the new GlobR2C2 (Global Recession Rates of Coastal Cliffs) database by taking advantage of all the existing site and regional studies, and built a worldwide cliff recession database. This database is used in a new approach to link documented erosion rates and external forcings.
It also allows researchers to look at the relative efficiency of forcings in relation to one another, in order to explain erosion rate variations at the global scale. The benefits of this global approach are that it erases local specificity and seeks to define global trends. The links between cliff retreat and environmental parameters were explored statistically. However, the synthetic database approach is limited in that it compiles the information available for all studies at once. In that sense, it reduces information to the largest common denominator. Therefore, the main goals of this paper are as follows: (i) to compile a review of online literature in English, French or Spanish from peerreviewed publications or national databases providing cliff retreat rates; and (ii) to link a dependent variable (erosion rate) to independent variables (cliff and meteo-marine settings).
Study design The main goal of this study is to link cliff retreat rate to external forcings at global scale. Those data exist in peer-reviewed journal articles and national databases. Peer-reviewed articles were chosen as the source of cliff descriptions and erosion rate values and settings. However, marine and continental forcings conditions are often reported in a very heterogeneous fashion. This information can either be completely lacking, incomplete or described in inconsistent ways. To overcome this issue, external global databases were used to harmonize forcings (i. e. , tidal range, swell height, rainfall and so on; see Sect. 2. 3. 6 to 2. 3. 9). They provide standard-ized and reputable information for cliff height, sea condition and atmospheric climate. The different steps of the study described in subsequent paragraphs are as follows: (i) the design and filling of a relational database with raw data, (ii) post-processing on database fields in order to tidy up the data and (iii) statistical exploration of links between erosion and forcings.
Database design To organize the disparate knowledge reported in the literature, a rigorous analytical framework is an absolute necessity upstream of any data capture. We opted for a relational data base framework where the architecture was designed according to the Merise method  (Tardieu et al. , 1985). Merise provides a formal methodology to describe entity-relationship data models. Each entity corresponds to a group of data framed into a table and containing different fields called attributes. The different entities are related to each other by well-defined relations. As an example, the "cliff" entity contains information about cliff settings (Fig. 3 ). Each cliff description corresponds to a line in the "cliff" table and contains a unique primary key to identify this line/record. The "measure" entity contains information about cliff erosion.
"Cliff" and "measure" are related through cliff erosion. The relation between an erosion record and its corresponding cliff is made by typing the cliff primary key. This conceptual exercise allows for optimized data capture and redundancy, the flagging of possible information duplicates and the limitation of ill-conceived relationships. The database structure was implemented in OpenOffice. org Base, which can be addressed by the statistical software R via SQL queries. Only the geographic fields (cliff location) were digitized in Google Earth and exported into shapefile with a key code or primary key linked to the relational database (in the sense of data science analysis). Here, GlobR2C2 was structured with two objectives in mind: (i) compiling original information and faithfully tracing publication sources, and (ii) anticipating analytic queries of the database designed to answer geomorphological questions.
The database is structured to keep track of information relative to publications, sites, measurements and contextual information of the cliffs, or their environment. Specific care was taken to separate original data from information derived by us, and to distinguish between article information from auxiliary datasets (Fig. 3 ). The database contains entities from three type of sources: raw data from publications, raw data from gridded data (global reanalysis) and tidy covariates (derived from raw data). The final conceptual data model contains 11 entities and 76 attributes. A conceptual model is given in Fig. 3. Entities refer to publications ("Publication and Author"), cliffs ("Cliff, Lithology, Geotechnical parameters, Cliff height"); erosion rate measurement ("Measure") and forcing ("Climate, Swell, Tide").
Raw data extraction: from publications and national databases GlobR2C2 (Global Recession Rates of Coastal Cliffs) database v1. 0 was populated with data from two main types of published sources: published peer-reviewed English journal articles, and official but non-peer-reviewed studies arising from official organizations (e. g. , the CEREMA French risk survey) in English, French or Spanish. Journal articles were selected when they reported quantified values of cliff recession rates and described the quantification method. The search was initiated with bibliographic web search engines (Web of Science, Google Scholar) and expanded using citations therein. We recognize that some references may have escaped our attention. We are keen to expand the database further with the contribution of the community.