dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We are indebted to  Catherine Andre(IGDR ,  CNRS-UMR6290 ) for providing samples from the  CaniDNA Biobank. We express gratitude to  Joanne Burden  who kindly proofread the English and Gregory Ruz from Seevents who prepared Figure 1. We thank the archeologists  Stephanie Brehard  ( MNHN Paris ),  Laure Salanova  ( CNRS-UMR7055 ),  Dragomir Popovici  ( The National Museum of Romanian History, sites Hars ¸ova and Bordus ¸ani ),  Cristian Micu  ( ICEM, Tulcea, site Isaccea ) and  Sta ˘nica Pandrea  ( Archaeology Braila Museum, Romania, site Silistea ) for the material they generously provided and the veterinarians solicited for samples from modern breeds. We also thank  PALGENE , the  French National Platform of Paleogenetics. Sequences generated in this paper have been deposited in the GenBank Data Library under accession numbers  JQ971988  to JG972027 and  JX273571-JX273640.
Data collection For every patient presenting on a given day at their practice, participating GPs were asked to fill out a standardised questionnaire on age, gender, vaccination status against seasonal influenza (in 2009-2010 and 2010-2011), pandemic influenza in 2009-2010, and presence of risk factors for severe influenza illness, as defined by French health authorities (Table  1 ). Data on both chronic conditions and immunization status were reported by the GPs without any written confirmation. Data were obtained either by asking to the patient and/or using data from their medical records. ] In addition, data were collected on age, gender, region of exercise for participating GPs. Regions of exercise were categorised in rural or urban areas according to the mean number of inhabitants (urban municipalities are municipalities without continuous built area of 2000 inhabitants, and those with less than half of the municipal population is in an area of continuous built, as defined by the French Institute of Demography  [6] ).
Hence the importance of the involvement of the specialists in the promotion of vaccination in patients with specific risk factors (such as pregnancy, severe pulmonary, cardiac and renal diseases). In our study population, 14% of patients were obese, and 11% in those aged <65. More than 50% of them had no other risk factor for severe influenza. Obese poorly vaccinated were those under <65 years for seasonal flu and all subjects of this sample for pandemic influenza. It must be noted that there is no data in the literature on the obese influenza vaccination coverage. Sample sizes were low in other target groups, thus estimates of VC should be interpreted with caution in these categories. Forty four pregnant women could be evaluated for both influenza seasons in our study population. VC for seasonal and pandemic influenza vaccines were particularly low (5-7%).
However, the Sentinelles network is composed by volunteer GPs who collect real-time epidemiological data, suggesting a specific interest for public health, in particular for immunization. This limitation could explain the high vaccination rates observed, as compared to studies in general population. Third, since participation rate was relatively low, some target groups were less represented, leading to wide CI for rare target groups, in particular for HIV infection, other immunosupression, chronic renal disease and pregnancy. Patients of these categories probably get medical care from specialists of their chronic disease, hence underlining the importance of conducting specific studies in specialized medical services. And finally, immunization data were self-reported by the patient and/or the GPs and not writtenconfirmed, leading to some degree of imprecision in evaluation of the immunization status.
Indeed, estimation of VC was based both on answers of patients and on data collected by the GPs in their medical records. Usually, participation biases are in favor of better vaccinated individuals, leading to some over-estimation of coverage in the telephone surveys. The prevalence of chronic conditions in our study sample was comparable to that estimated in the general population regarding data published by the French Ministry of Health  [33]  for pregnancy, obesity, diabetes mellitus, Sidainfection and chronic cardiac diseases (prevalence estimates of 1%, 13% 4%, 0. 05% and 1% respectively in the general population). Persons aged 65 and over were overrepresented in our sample, whereas prevalence of chronic bronchopulmonary and renal diseases were low, maybe due to underdiagnosis. This confirms that for most chronic conditions, involvement of GPs can have a potentially important impact to improve VC.
research grants. Thanks to the Arkeologi Museoa (Bilbao), its director and all its staff for their help in the revision of the faunal remains. The 14 C dating of Atxuri was possible thanks to the permission of the Eusko Jaurlaritza. Thanks to J. Maroto, M. Dachary, P. Arias, K. Mariezkurrena, J. Altuna, S. J. Pereda, P. Alcázar, J. Estévez, F. Bernaldo de Quirós, A. Ruiz-Redondo, A. B. Marín, J. Yravedra for providing important information on sites and for discussion. Thanks to the reviewers and to the editor J. Piotrowski for their useful comments, that have improved this paper. M. Hernández and E. Pomeroy kindly revised the English and provided useful comments. Eusko ikaskuntza provided funding to study the faunal remains of Arlanpe. AGO has Marie Curie-IEF research fellowship and is supported by the Ministerio de Economía y Competitividad (project CGL2012-38434-C03-01).
Acknowledgements. Thanks to the Arlanpe excavation and research team for their help in the field and fruitful discussion. Excavations at the Arlanpe site were funded by  Bizkaiko Foru Aldundia ,  Fundación José Miguel Barandiarán  and  Harpea Kultur  elkartea. Thanks to  Lemoako Udala  for all their help. The research on the faunal remains of Arlanpe has been supported by Eusko.
We are interested to investigate which dimensions of a user's online representations are most relevant for mining his credibility, if it is possible to combine multiple dimensions in order to improve the mining process, if credibility mining can be deployed at large scale and how can user credibility scores be used in other applications, such as a re-ranking method in an information retrieval system. A first valuable resource for our studies is represented by the question answering communities where introducing a credibility component could provide a fast indicator for selecting the better answers. Since information streams provided by Web 2. 0 users are formed of different types of media, another choice to test our approach to credibility mining is on Flickr data where credibility is derived using a combination of structural factors and content analysis.
Procedure Several studies based on the Lorhandicap survey data have already been published  (Baumann et al. 2007; Chau et al. 2009; Lemogne et al. 2012). The initial sample consisted of subjects aged 15 years or more living in 1996 in 8,000 randomly selected households in the Lorraine region of north-eastern France (2. 3 million inhabitants), representing 1/100 of the population. The investigation was approved by the Commission Nationale de l'Informatique et des Libertes (national review board), and a written informed consent was obtained from the respondents.
Follow-up The cohort was followed up for mortality from 1st July 1996 to 31st December 2008 (12. 5 years). The vital status of all subjects was ascertained from the national computerized database listing all deceased subjects in France from 1978, by contacting the registry offices of the birth places for people born in France and by contacting the registry office for foreign-born French citizens (Ministry of Foreign Affairs). Causes of death were coded by the French national cause-of-death registry (INSERM) using the current revisions of the International Classification of Diseases. Violent mortality corresponds to codes E800. 0-E999 (8th or 9th revision) or V01. 0-Y89. 9 (10th revision) and comprises suicides, homicides and accidental deaths. Nonviolent deaths comprise all other deaths.
The contributions of self-reported health and those of behavioural risk factors were estimated by the changes in the HRs, derived from the formulas: (HR model 1 -HR model 2 )/ (HR model 1 -1) and (HR model 1 -HR model 3 )/(HR model 1 -1), respectively. The proportional hazard assumption was evaluated from Schoenfeld residuals for the global model and for each covariate. The statistical analyses were performed using STATA software (Stata, College Station, TX, USA).
Acknowledgments Lorhandicap study group:  N. Chau ,  F. Guillemin ,  J. -F. Ravaud ,  J. Sanchez ,  S. Guillaume ,  J. P. Michaely ,  C. Otero Sierra ,  B. Legras ,  A. Dazord ,  M. Choquet ,  L. Mejean ,  N. Tubiana-Rufi ,  J. P. Meyer ,  Y. Schle  ´ret and  J. M. Mur. The authors would like to thank  D. Saouag ,  M. Weiss ,  M. Depesme-Cuny  and  B. Phe  ´lut for their help during the survey. The work was supported by a Grant from the  Pole Europeen de Sante.
Socio-economic data Socio-economic and demographic data were obtained from INSEE (1999) at census block level (Table  1 ). In order to characterize the socio-economic neighbourhood level, we used: i) in a first step, a deprivation index, and ii) in a second step, an array of specific socio-economic variables (including education level, employment and occupation status, and housing characteristics). Principal-component analysis was used to create the deprivation index based on the approach described in Lalloué et al. [47].
Noise exposure data Noise exposure modelling In 2007, in accordance with requirements from the European Environmental Noise Directive (END, 2002/49/ EC)  [48] , noise nuisances were measured and modelled across the Lyon metropolitan area by the urban Community of Grand Lyon using the GIpSynoise software  [49]. The model used follows two stages. First, an acoustic calculation using CadnaA (Computer Aided Noise Abatement), which is a model-based computer program developed by DataKustik (Greifenberg, Germany)  [50] ; and second, generation of people exposure, using GipSynoise. The calculation model (CadnaA) incorporates four specific methods recommended by END for calculating current noise levels: (i) NMPB/XPS31-133 (French national computation method -1996) for road noise; (ii) NMPB -Fer (NF S31-133 :2011 for railway noise  [51] ; (iii) ISO9613 (Acoustics -Attenuation of sound during propagation outdoors-) for industrial noise; and (iv) ECAC.
Spatial methodology To evaluate the spatial implications of adjustment for neighbourhood characteristics (noise and deprivation level) on the spatial relocation and provide an explanation of infant mortality risk across Lyon Metropolitan area, the most appropriate approach is spatial method using the spatial scan statistic  [53]. We investigated presence, relocation and explanation of spatial distribution of the risk of infant mortality by cluster analysis -the spatial scan statistic implemented in the SaTScan software  [54]. This approach, which is used in an increasing number of applications in the field of spatial epidemiology  [55] , allows exploration of the presence of high risk infant mortality clusters (named 'most likely clusters') and their spatial location. The number of cases in each census block is assumed to follow a Poisson distribution.
The third limitation concerns the noise data used in the analysis. The modelling technique calls for information on topography, land use, road traffic, population, etc. that may be collected at different periods, leading to uncertainty in matching all the data. Another source of uncertainty is the population calculation for each residential building (Pop Bat j. i ) which is computed in proportion to the volume of each building within each census block. For instance, each inhabited building with a height lower than 4 metres is considered to be 4 metres high, according to the methodology used to predict noise levels using the GIpSynoise software  [138]. However, compared to crude average, our noise exposure indicator was built to obtain a noise value weighted by the resident population in each building for each census block.
Acknowledgements This project is funded by the  French National Research Agency (ANR , contract- 2010-PRSP-002-01 ). This work was supported by the  French Environment and Energy Management Agency (ADEME)  through a  doctoral grant for Cindy. M Padilla. The authors thank all of the organizations that kindly provided the data used in these analyses: especially the  Scientific and Technical Centre for Building (CSTB)  and the Grand Lyon metropolitan authority. We thank  Michael Osei MIREKU  for his idiomatic editing of the paper. We thank  Pr Clive E Sabel  and  Pr Martin Kulldorff  for their valuable advice and guidance in this work.
opinion article has benefited from discussions held at the IPCC Expert Meeting on Geoengineering that took place in Lima, Peru on 20-22 June 2011, which four of the authors attended. PMF and NEV would like to acknowledge support from the EPSRC/NERC for the IAGP project. OB, ML, TML, AM, and NEV would like to acknowledge partial support from the FP7 EuTRACE project grant agreement (306395). AM and ML would additionally like to thank the German Ministry for Education and Research (BMBF), the Brandenburg Ministry for Science, Research and Culture (MWFK) and the Research for Sustainability Platform (FONA). OB acknowledge supports from the Agence Nationale de la Recherche under the REAGIR project. NG acknowledges the financial support of ETH Zurich. The authors would also like to thank Jim Haywood, Thomas Leisner, Helene Muri, Rodrigo Riestein, Simon Shackley, Harald Stelzer for useful discussions and for responding to the questionnaire.
Microwear Analysis After initial examination, many specimens were excluded from analysis because they were physically altered during transportation or compaction of sediments  [116]. Since microwear patterns may vary from mesial to distal teeth, the analysis is preferentially restricted to upper and lower M1s and M2s. The dental microwear patterns of fossil taxa were compared to those of extant grazing and browsing ungulates including artiodactyls and perissodactyls (Tables  S4  and Figure   4 ). All microwear signatures of this study were only determined by one experienced observer (G. Merceron) to avoid any potential inter-observer error  [117]. Regarding dental microwear analysis, several protocols were developed to quantify occlusal wear patterns at a microscopic scale. Differences concern casting procedures applied and the data acquisition.
In this convention, a score of 0 represents the most attrition-dominated mesowear signature, while a score of 4 would represent the most abrasion-dominated signature. Individual scores were averaged and a mean score was calculated for each species (Fig. 3 ). Scores thus indicate the over all abrasiveness of the diet a species has to cope with. As comparative dataset, we consider the medium-size ungulates (artiodactyls and perissodactyls) with sample size clustered in broad diet categories (Figure  4 , Table  S5 ). excavations 1996-2000 of the Forschungsinstitut Senckenberg at Eppelsheim into this study. Furthermore we would like to thank Dr. Burkhard Engesser who provided the hipparionine teeth from Charmoille for the stable isotope analyses. Finally we thank Matt Mihlbachler and one anonymous reviewer for their constructive comments that helped to improve the manuscript significantly.
Acknowledgments We thank the  Forschungsinstitut und Naturmuseum Senckenberg (Frankfurt) , the  Staatliches Museum fu ¨r Naturkunde (Karlsruhe) , and the  Landesmuseum Rheinland-Pfalz (Mainz) , the  Collections d'Histoire Naturelle de l'Universitede Lyon  ( A. Prieur ) and the  Naturhistorisches Museum Basel (L. Costeur)  for access to the fossil specimens investigated in this study. In particular, we wish to warmly thank  Dr. Jens Lorenz Franzen  for allowing us to include the hipparion skeletal material from the.
This study was partly financed by the  Swiss National Science Foundation (SNF)  grant  200021-100530/1  to TV and the  Deutsche Forschungsgemeinschaft Emmy Noether-Program   TU 148/2  to TT and  KA-1525 4-1/4-2  and  KA-1525 9-1 ,  KA 1525 8-1  to TMK and is publication no. 44  of the  DFG Research Unit 771  ''Function and enhanced efficiency in the mammalian dentition-phylogenetic and ontogenetic impact on the masticatory apparatus''. The study was further funded by a research grant from the  Fyssen Foundation (Paris, France)  to GM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
To pursue our study, we collect data on teaching methods across schools from several international data sources. The three data bases we examine are 1) the Civic Education Study (CES), run in 1999 in 23 countries to assess the level of civic knowledge of mostly 14 year olds in the 8 th and 9 th grades, 2) the Trends in International Mathematics and Science Study (TIMSS), conducted in 1995 in 33 countries and focused similarly on the 8 th graders, and 3) the Program for International Student Assessment (PISA), which we use for 2000 and 2003 waves for 15 year olds in 36 countries. The CES data in particular contains a great deal of student-specific information about student beliefs and characteristics, as well as characteristics of their teachers and their schools, including most importantly teaching methods.
In our empirical work, we emphasize the distinction between "students copying from the board" and "students working in groups" as measures of vertical and horizontal teaching methods. We can then use CES at the student and school level to relate teaching methods to student beliefs, and use all data sources at the country level to relate teaching methods to a variety of measures of both beliefs and social outcomes. In doing so, we seek to address four questions. First, do teaching methods vary systematically across countries? The answer to this question is a clear yes. Second, do teaching methods matter for student beliefs? The answer is again a clear yes. There are very strong correlations between teaching methods and student beliefs both in a cross-section of countries, and more importantly, in a cross-section of students in the CES sample, holding country fixed effects, as well as a variety of student, school, and teacher characteristics constant.
Database We combine three main international databases to analyze country differences in teaching practices. The first database is the "Civic Education Study" (CES), based on a survey run in 1999 by the International Association for the Evaluation of Educational Achievement (IEA). The CES is designed to assess the civic knowledge of students in grades 8 and 9 in 23 countries. The study covers  Australia, Bulgaria, Colombia, Cyprus, Czech Republic, Denmark, England, Estonia, Finland, Germany, Greece, Hungary, Italy, Latvia, Lithuania, Norway, Portugal, Romania, Russian Federation, Slovak Republic, Slovenia, Sweden, Switzerland, United  States. The sample covers 140,000 students, 9,000 teachers and 4,000 school principals. The assessment is designed to measure various dimensions of civic knowledge, including concepts of democracy and citizenship, attitudes to institutions, trust and civic-related actions, as well as beliefs about cooperation among students and cooperation between students and teachers.
In addition to the individual student survey, the CES includes school-principal and teacher background questionnaires. Critically, the teacher questionnaire requests detailed information on teaching practices of the teachers. Each of the participating countries randomly samples the students to be surveyed using a two-stage stratified sampling design. The primary sampling unit (PSU) is the schools randomly selected in each country. The students from grade 8 (or 9) are then randomly picked from the assigned class in the selected school. The teachers of those selected students completed individual surveys (as did school principals). For students with multiple teachers (up to a maximum of five in the database), all the teachers completed the questionnaire. The individual teacher surveys asked the following questions about teaching practices: « In your class, a) How often do students work in groups? b) How often do students work on projects ? c) How often do students study textbooks? , d) How often do students participate in role play, e) How often does the teacher lecture? , f) How often does the teacher include discussions, g) How often does the teacher asks questions? ».
The answers take on values 1 for Never, 2 for Sometimes, 3 for Often and 4 for Very Often. The second international database is the Trends in International Mathematics and Science Study (TIMSS). The TIMSS is a cross-country comparative test of student cognitive achievement in math and science, conducted in 1995 by the IEA, the same international consortium that constructed the CES database. TIMSS is also targeted to students belonging to grade 8 th and cover 33 countries: Australia, Austria,  Belgium, Bulgaria, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Indonesia, Iran, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Netherlands, Norway, Portugal, Romania, Russia, Singapore, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United  States.
The database combines information from student, school-principal, and teacher questionnaires for representative sample of students. Unlike the CES, the TIMSS database does not have specific questions on student beliefs, since the primary focus of this study is the assessment of cognitive performance. However, the student questionnaire does ask specific questions about teaching practices for a larger and more diverse group of countries than the CES. Teaching practices are measured from the individual student surveys conducted in all classrooms in each selected school. The survey covers the classes in mathematics, science, biology, chemistry and earth science. We focus on teaching practices in mathematics, which allow observations for the maximum number of countries. The appendix reports results for practices in other classes, which turn out to be highly correlated within each country.
In contrast, East European and Mediterranean countries display a higher share of teachers reporting that they lecture most of the time. Figure  1  also suggest that in countries such as Germany and Switzerland teachers combine the two practices, or do something else with their class time. To get a more comprehensive picture of the different patterns across the various teaching practices, we run a factor analysis on the six practices reported in the CES database. Table  1a  documents the correlation between the different teaching practices. Table  1b  shows the factor analysis that leads us to select two mains factors for clustering the teaching practices. We call the first factor Vertical Teaching, to capture situations in which teachers tend to lecture, ask the students questions, and ask the students to work alone on their textbook.
We call the second factor Horizontal Teaching, to capture situations in which the teacher tends to ask students to work in groups, work on projects, participate in events and role play, and have discussions. Together, these two factors explain 82 percent of the cross-country variance in teaching practices. Figure  2  shows the cross-country relationship between the indicators of Vertical Teaching and Horizontal Teaching from the CES database. Vertical Teaching is measured by the first principal component of the practices "Teacher lectures", "Teachers ask questions", and "Teachers ask students to work alone on their textbook". Horizontal Teaching is the first principal component of the practices " Students work in groups", "Students work on projects", "Students work in plays", "Teacher discusses with students" and "Students participate in events".