dataesr/scientific-paragraphs-categorization huggingface dataset:
Background. Although rotavirus vaccines have proven to prevent the risk of rotavirus gastroenteritis (RVGE) in children under 5 years old, they are also associated with an increased transient risk of intussusception (IS). Several quantitative benefit-risk models (qBRm) are performed to measure this balance in hospitalizations and deaths prevented versus the ones induced. Method. In this study, our objective was to provide a complete overview of qBRm used for rotavirus vaccination. We systematically searched 3 medical literature databases to identify relevant articles, in English, that were published between 2006 and 2019. Results. Of the 276 publications screened, 14 studies using qBRm for rotavirus vaccination were retained, based on preselected criteria. Four were performed in low-and middle-income countries.
Search Strategy We systematically searched Medline, Scopus, and the Institute for Scientific Information (ISI) Web of Knowledge databases to identify original studies on qBRm for rotavirus vaccination published from January 1, 2006 to December 13, 2019. The search strategy used prespecified terms ("benefit-risk" and "rotavirus vaccines"), as detailed in Appendix Table  1 , and was limited to publications in English. Two reviewers (H. A. and N. P. ) independently screened all titles and abstracts using predefined criteria (Appendix Table  2 ). Subsequently, the assessment for eligibility of identified publications was carried out by examining their full text. Disagreements between the 2 reviewers were resolved through discussion. In addition, reference lists of eligible articles were screened (ie, "snowballing") to identify potential additional publications.
Data Extraction and Analysis The following data were extracted and summarized: the qBRm general information, the model characteristics, the input parameters, and the BR estimates. General information includes the studied vaccine(s), the alternative(s) to the studied vaccine(s), the vaccine funding sources, and the income category of the countries for which the BR was estimated. The model characteristics were classified according to the 8 attributes  [34] [35] [36]   The population's behavior in the model is simulated using population's averages (aggregate data) or considering each individual's attributes (individual-based data). 8. Model including Scenario/Sensitivity analyses or Not: scenario (using analyses to investigate different epidemiological or healthcare scenarios of interest) and/or sensitivity (using analyses to quantify the range of uncertainty) analyses were conducted or not.
This finding might be due to differences in healthcare infrastructure or delays in care  [7]. The present review systematically collected the published information on qBRm for rotavirus vaccination, which allowed further characterizing its BR profile. All selected studies concluded that vaccine-prevented RVGE-related hospitalizations and deaths outweigh vaccine-induced IS-related hospitalizations and deaths, with no marked difference between LMICs and HICs. Differences in BRR noted across studies included in this review can be explained by  (1)  the choice of model attributes (eg, simulation versus nonsimulation models), (2) varying epidemiology of RVGE and IS observed across countries and areas, (3) data availability at the time of the study, and (4) differences in the choice of input parameter values.
Acknowledgments We thank  Emmanuelle Ghys  ( XPE Pharma and Science ) for editorial assistance and publication coordination on behalf of GSK. Financial support. This study was conducted as part of a PhD program funded by  GlaxoSmithKline Biologicals SA  and the  Association Nationale pour la Recherche et la Technologie (ANRT) ,  Paris, France. Potential conflicts of interest. H. A. , G. N. , and N. P. are employed by the  GSK  group of companies, which produces 1 of the vaccines of interest (Rotarix) in this review. G. N. and N. P. also hold shares in the GSK group of companies. All authors have submitted the  ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
The MEDITS data have been used for joint publications, which have elucidated several aspects related to   vey (1994-1999) "  (Abelló et al. 2002 ) is the earliest good example of a joint publication at the wide geographical scale of the northern Mediterranean. Furthermore, studies have been carried out to understand the impact of fishing pressure on the abundance of populations, fish community diversity and structure, as well as to investigate the influence of environmental drivers on shaping the spatial and temporal distribution of fish populations and their communities, thus helping forecast the effects of global changes at a Mediterranean scale. Taxonomic studies, including new reports in the area and descriptions of new species, have also been carried out from samples collected during MEDITS surveys.
A list of relevant publications is provided in the Supplementary Material. Twenty-five years after the beginning of the MED-ITS trawl survey, this second monograph aims to further understanding spatial and temporal patterns of populations and fish community structures and to explore the influence of anthropogenic factors in shaping such patterns. This paper aims to summarize and update the specifications of the MEDITS trawl survey, focusing on those most relevant to an ecosystem approach to fishery management and on data quality. The latter is pivotal for a sound evaluation of the status of demersal resources and their communities.
Haul duration is 30 minutes on the continental shelf (10-200 m depth) and 60 minutes on the slope (201-800 m depth). The standard fishing speed is 3 knots on the ground, and hauls are allowed only during daytime. Haul performance and gear geometry are usually monitored using the SCANMAR system or, more recently, SIMRAD or MARPORT sensors. Data acquisition is monitored in real time using a laptop and specific software. Effective tow duration was considered as the interval from the time when the gear is stabilized on the bottom and the time when speed is reduced to recover the warp. Vertical and horizontal openings (wings) of the net working on the bottom are expected to range from 2 to 3 m (more commonly 2 and 2. 5 m) the former and from 15 to 22 m the latter, the higher values depending on depth.
The time of the year in which the MEDITS survey is scheduled is late spring-summer (from May to July). The survey follows a depth-stratified random sampling scheme, with haul allocation being proportional to the surface of depth strata, whose limits are 10-50, 51-100, 101-200, 201-500 and 501-800 m. Up to 44 different geographic sectors are also included in the stratification. The sampling strata and the GFCM GSAs are reported in Figure  3. Indices are calculated following the usual procedure of the stratified mean and variance  (Souplet 1996) : ∑ = = I Wx i i i N 1 ∑ ∑ = - = = I W S A f var( ) ( 1 ) i x i j j n i N i 2 2 , 1 1 i i R scripts have been developed for estimating population indices. These scripts are available at https:// www. coispa. it/index. php?option=com_content&view =article&id=34&Itemid=119&lang=it.
However, since the advent of the DCF, some changes have occurred: i) an increase or a decrease in the sampling intensity from the period 1994-2001 to the subsequent one; ii) a deviation of the survey season from the standard one in certain areas and years; and iii) vessel replacements without the possibility of performing field intercalibration tests. For all these reasons, modelling through GLM, GAM, Delta-GLM and Delta-GAM was suggested, both for the standardization of abundance and biomass indices and for the length-frequency distributions. R scripts have been developed for those purposes and are available at https:// www. coispa. it/index. php?option=com_content&view =article&id=34&Itemid=119&lang=it.
SUMMARY OF THE MEDITS BIOLOGICAL SPECIFICATIONS The focus of the collection of survey data has been on keeping consistency throughout the time, so revisions of the protocols were introduced taking care to avoid disruptions in the time series. These changes are proposed, discussed and adopted in the MEDITS coordination meetings, which are organized annually. During the last few years more emphasis was directed towards addressing ecosystem questions, while placing the survey in the DCF. Since 2012, the taxonomic categories and lists have been expanded to take into account the needs of the Marine Strategy Framework Directive (MSFD; Directive 2008/56/EC). All the species larger than 1 cm caught during the MEDITS survey are identified, then total weight and number of individuals are recorded. Alien species are also identified and noted.
DATA COLLECTION ON MARINE MACRO-LITTER In 2013, the MEDITS coordination meeting decided to introduce among the MEDITS activities the samplings of marine macro-litter, to provide data for the descriptor 10 of the MSFD. A common protocol, taking the basis from the one of  Galgani et al. (1996) , was hence established for the collection of these data on a voluntary basis and it was further improved in 2014 and 2015. Up to 34 different typologies have been identified in the protocol, including 9 main categories related to litter material class and 27 sub-categories related to source and main litter findings (Table  4 ). This table also shows a comparison with the classification adopted by the ICES International Bottom Trawl Survey (IBTS). As a result of this activity, the MEDITS group also contributed to the actions of the United Nation Environment Programme (UNEP), the Barcelona Convention of the Mediterranean Action Plan (MAP) for implementing the Regional Plan on Marine Litter Management in the Mediterranean, and the Marine Litter Regional Cooperation Platform.
MEDITS DATA QUALITY The MEDITS protocol also establishes common formats for data storage, which include the following standard files: TA (data on the technical specifications of the hauls), TB (aggregated data on total number and weight by species), TC (aggregated data of the frequency distribution by length, sex and maturity stage by species), TE (individual data of length, weight and age by sex) and TL (data by category and subcategory of marine macro-litter). The Common Fisheries Policy sets out key principles for data quality: e. g. accuracy, reliability and timeliness, avoidance of duplication through improved coordination, safe storage in data base systems and improved availability (EC 2013). To minimize the occurrence of errors, in addition to the standardization of data collection using common protocols at the different steps of the survey implementation, common data checks on the MEDITS standard files were implemented.
In 2011, the process of data quality checks was updated and standardized among the MEDITS group to unify the checks independently made by the 18 GSAs participating in the MEDITS survey. To perform automatically the data check procedure by means of a routine enabling errors to be detected and facilitating their correction, the RoME routine, an R code for performing multiple and cross checks on MEDITS survey data in TA, TB, TC, TE and TL files, was developed  (Bitetto et al. 2019). In version 1. 3, RoME was transformed into a package structured in 55 different functions: the run is performed by means of the function RoME(). Each function is related to a specific check and is recalled in a specific order to avoid cascade errors. This is also maintained in RoME version 1. 4. This software does not correct the data, but it detects the errors, warning the user that there is the possibility of one or more errors, specifying the type of the error and facilitating correction of the data.
The process is based on a loop of checks (errors and warnings) and feedbacks, so users are able to correct data but they are also advised if some deviations from the protocols occur that are not necessarily classified as errors. This also represents the basis for a data quality assurance and audit for the data to be used in the MSFD  (Moriarty et al. 2019)  and in the data calls of end users. The analysis carried out at EWG-STECF level evidenced that the quality of MEDITS data greatly improved when RoME was used before data upload and the Joint Research Centre checks correctly show no error patterns  (STECF 2013). The data checks are performed by RoME simultaneously on the files that can also contain data of more than one year. Further specifications can be found in the RoME Manual, which can be downloaded together with the software at the following link: https://www.
sibm. it/MEDITS%202011/ principaledownload. htm. Another point which can be a source of bias is related to the gear used during the survey, i. e. whether the technical specifications are in line with the standards adopted for the MEDITS gear. The Multidisciplinary Group on Gear Performance and Standardization of Gear Data Processing (MGGP) was established within the MEDITS coordination group. Regular checks of the MEDITS gears (trawl, rigging and doors) were introduced in 2012, and this protocol of checks was updated in 2014 and further revised in 2015 to fix some technical details. The final version is reported in the MEDITS Handbook, which also includes the work performed by this working group (MEDITS-Handbook. Version 9, Anonymous 2017).
ACCESS TO MEDITS DATA Access to the MEDITS data is currently controlled by regulation EU 2017/1004 (recast). Data are made available for end users' needs (e. g. STECF, GFCM) through specific data calls released on an annual basis. Data can also be made available by the relevant countries for specific projects. To facilitate scientific collaborations, each year the MEDITS coordination group agrees common projects, including scientific publications based on the MEDITS data. In addition, through contacts with the international and national coordinators, a certain number of scientists not involved in the MEDITS project can be invited to the annual MEDITS coordination meetings to present proposals for common projects and discuss the preparation of scientific papers.
MEDITS DATA FOR FISHERIES ASSESSMENT In the Mediterranean, until the advent of the DCF, trawl survey data were considered the most important-and sometimes the only-source of reliable information for evaluating the status of stocks, fish communities and ecosystems using total mortality estimates (e. g. SAMED;  Lembo 2002) , assessment models based on fishery-independent data (e. g. SURBA; Needle 2003), simulation models (e. g. ALADYM;  Lembo et al. 2009 ) and population and community indicators  (Cotter et al. 2009a). Under simple formulation and assumptions on natural mortality, MEDITS data allow estimates of total mortality to be made from the structure of the species population at sea, so that guess estimates of the exploitation rate can be obtained, an approach that is also valid in data-limited situations.
FINAL REMARKS The strength of the MEDITS survey so far has been the agreement among the participants to share standardized methods at a Mediterranean level using the same gear, sampling scheme and protocols for collecting, checking and analysing data. However, a shift in the survey time occurred in some situations, and the survey could be not conducted in some years because of administrative issues at national level. Implementing mitigation actions through standardization methods based on GAM modelling is possible, but this process is time-consuming and not always successful. Hence, an effort should be made to avoid disruptions in the time series of surveys as much as possible. The experience gained in MEDITS in terms of standardization of file formats (TA, TB, TC, TE and TL) and data quality checks can be used to move forward the implementation of a common database/platform to share the effectiveness of open source visual and statistical data checks, keeping internationally available and maintained standard reference lists, sharing data for process and upon end users' requests.
In fact, data accessibility and availability for scientific use is also considered a key point in the European Union (STECF 2018c). The experience gained in MEDITS in terms of data standardization and data quality checks can also be applied to recover time series of past surveys in the different countries, as was already done in the context of the RECFISH project  (Ligas 2019)  for the GRUND surveys  (Relini 2000). During the last few years, a liaison with the ICES Workshop on Technical Development to Support Fisheries Data Collection (WKSEATEC) and IBTS took place. While progress in the Mediterranean has centred on implementation of standardized data checking routines across surveys, in the Atlantic and Baltic areas efforts converged towards progress in electronic data capture. Moving towards a wider implementation of paperless sampling during the measuring process using either purchased or developed in-house technology is a point to be further developed for the future in all the Mediterranean GSAs involved in the MEDITS project.
A question also rises on the use of data from scientific surveys such as MEDITS. Is the potential of this kind of information fully exploited? The usefulness of the MEDITS trawl survey time series also relies on the possibility of using these data in an assessment framework that allows them to be exploited to produce advice, even in situations in which fishery-dependent data are not available, as is being done in the ICES advice framework (Table  5 ). Trawl surveys are also an accurate source of information for understanding the influence of climate change on fish populations, their communities and ecosystems. Many papers so far have tried to disentangle the effects of the anthropogenic pressure caused by fishing from the ones mainly driven by environmental variables linked to climate change, such as sea surface and bottom temperatures, using GAM modelling for example.
All of these challenges will be made possible thanks to databases, gathering longitudinal data that measure accurately sex differences in lifespan, which are becoming increasingly available (e. g. ,  [2] ). Several databases recording the number of pathogen species found in mammals, such as the World Register of Marine Species (WoRMS i ), Pathogen-Host Interactions (Phi-base ii )  [50] , or the Database of Bat-associated Viruses (DBatVir iii )  [51] , have been developed. These databases provide a large amount of information about the diversity and the richness of parasites across mammalian species displaying contrasted lifestyles. Combining these databases should allow better understanding of the role of pathogens in between-sex differences in lifespan and aging (e. g. , in terms of both onset and rate of actuarial and/or reproductive senescence patterns) across mammalian species (Box 3).
Nuclear magnetic resonance (NMR) analysis In order to confirm the nature, the purity and the presence of possible other organic substances of the adrafinil powder bought on the Internet, a nuclear magnetic resonance (NMR) analysis was achieved, following method previously published  [4, 5]. Briefly, the NMR spectra were recorded on AVANCE 300 (Bruker Biospin, Wissembourg, France) operating at 300 MHz equipped with a 5 mm quadruple nucleus probe (QNP) at 295 K. The 1 H spectra were recorded with 64 scans, 32-K time-domain data points with 4 800 Hz spectral width, an acquisition time of 3. 42 s, a relaxation delay of 2 s and a flip angle of 30. The free induction decays (FIDs) were transformed (0. 3 Hz broadening) and the baseline was corrected. 7. 5 mg of powder was dissolved in 600 mL of methanol-d 4 and the ERETIC (Electronic REference To access In vivo Concentrations) method was used for the determination of absolute concentrations of adrafinil.
Statistical treatment Data acquisition was carried out on a computer with Fizz software  (Biosystèmes, 1990). Data analysis was performed using the XLSTAT software (Addinsoft, Andrenarcht, Germany, 2017) and R version 3. 5. 1  (R Core Team, 2016). The total duration of the evaluation, the consumption duration (time needed to swallow the yogurt) and the time before clicking on the first descriptor at the beginning of the test were extracted from the nonstandardized data. A two way anova with interactions was carried out with product and spoon factors considered as fixed effects and subject factor as random effect. If a significant difference was observed (α = 0. 05), the least significant difference (LSD) test was run to establish differences between means. Assessors exhibited different consumption behaviors with different.
For each product, the dominance rate (the proportion of subjects that selected each attribute) was computed at each time point on the standardized data, and TDS curves were represented over the three spoons. As TDS curves were performed on the standardized data, the differences of behavior observed between products regarding total consumption duration and time needed to click on the first descriptor were hidden. However, a higher consensus was obtained between judges, and the comparison between texture and flavor perception was made possible. A high dominance rate indicates a high consensus between the panelists at a given time. Dominance rate for each attribute was smoothed using a polynomial spline line type with the R package tempR  (Castura, 2016). It has to be noted that despite the smoothing performed on the dominance rates, clicking on the swallowing button induced a decrease of the dominance rate before swallowing.
It is worth noting that the analysis of dominance duration doesn't take into account the time at which the attribute has been perceived. Multidimensional differences were represented by a Principal Component Analysis (PCA) to compare the yogurt samples. Confidence ellipses obtained by bootstrapping the subjects, were drawn to represent the distribution of the evaluations by assessor around the mean. The spoons of yogurts were projected on the PCA in order to represent their evolution within each product. A PCA was also performed on the standardized data to show sensory trajectories over the time of consumption. Carrying out the PCA on the standardized data was important to enable the comparison between the texture modality and the flavor modality as their evaluation duration differed a lot.
According to the procedure described by  Lenfant et al. (2009) , the observations of the PCA performed on the standardized data were the dominant rates of each time-point and for each product. The variables were the sensory attributes. For the evaluation of texture, 4 equally-spaced time points were taken over the consumption period of each sample. As no attribute was dominant after swallowing, the time after swallowing was not taken into account in the analysis. However, for the evaluation of flavor, 4 equally-spaced time points were taken until swallowing, and another point was taken at the end of the evaluation to analyze the perception of the aftertaste. Two distinct PCA were performed to describe texture and flavor trajectories separately.
Acknowledgements The authors are grateful to regional councils of Brittany (grant n°1  3008651 ) and  Pays de la Loire  (grant  n°2014-07081 ) for the financial support, and  INRA for scientific coordination  ( J. Leonil ) through the interregional project  PROFIL , supported by  Bba  industrial association and carried out by the association ' Pôle Agronomique Ouest ". The authors would like to thank the company  Mane & Fils R&D  and  Mrs. Lizeth Lopez Torrez  and  Mrs. Solange Dalmas  for the help and advice for the formulation of the strawberry flavor.
Acknowledgment Clément Lozano is the recipient of a 50/50 match funding scholarship between the  University of Stirling (Scotland, United Kingdom)  and the  University of Sorbonne (France). We thank bio2mar platform (http://bio2mar. obs-banyuls. fr)for technical assistance and access to equipment. This work was supported by the  Carnegie   Research Incentive Grant  ( RIG008612 ). The funders had no role in study design, data collection and analysis, or decision to publish.