dataesr/scientific-paragraphs-categorization huggingface dataset:
One of the main objectives of this systematic review is to combine data from pertinent RCTs and prospective cohort studies to generate a pooled estimate of the absolute rate of recurrent VTE over standardised time intervals of 1, 2, 5, 10 and 20 years after stopping AT. Prior to pooling results, the research team will assess studies for clinical and methodological heterogeneity through comparison of important study characteristics including those related to the study design, patients and interventions. The degree of statistical heterogeneity will be measured and interpreted using a combination of Cochrane's Q (statistically significant at p<0. 10) and the I 2 statistic (>50% considered substantial). An I 2 value >75% is indicative of a very high degree of heterogeneity, and if encountered the data will not be pooled.
Data from RCTs and prospective cohort studies will also be analysed and pooled separately if applicable. In the event that quantitative pooling of cohort study data is inappropriate (due to clinical and methodological heterogeneity), findings from these studies will be compiled to synthesise a narrative. StatsDirect 27 will be used for meta-analyses and SAS software (V. 9. 4; SAS Institute, Cary, North Carolina, USA) will be used for meta-regression.
Measures of treatment effect Dichotomous outcome data (rate of recurrent VTE and major bleeding) will be quantified in terms of absolute risk. Due to variation in the duration of follow-ups in different studies, and the well-recognised fact that the risk of recurrence off anticoagulation varies considerably with time, standardised time intervals will be used to collect outcome data. The rate of recurrence in the study cohorts will be calculated from each study based on the number of recurrent VTE events and the total number of patient-years of follow-up accumulated during Open Access the standardised follow-up periods after stopping AT. For RCTs, each study arm will be treated as a separate cohort. The total number of recurrent VTE events and number of patient-years across all studies will be pooled together to obtain a weighted estimate of the absolute rate (events per 100 patient-years) over standardised time intervals of 1, 2, 5, 10 and 20 years.
Planned sensitivity analyses We acknowledge the potential for outliers among the larger collection of studies with respect to the effect estimates. As part of the sensitivity analyses, such outliers will be removed from meta-analysis and the change in summary estimates will be recorded. Substantial changes in summary estimates will prompt the investigation of the outlier, with a particular focus on possible factors that explain the variation. Additionally, although not an anticoagulant, aspirin has been shown to reduce the risk of recurrent VTE by approximately 30% as compared with placebo in patients with unprovoked VTE. 28 As such, a sensitivity analysis excluding data pertaining to studies in which patients received aspirin after discontinuing AT will be performed. Further sensitivity analysis will entail addressing the risk of bias present among included studies.
Acknowledgements FK, MC, CK, SS and MAR are members of the  Canadian Venous Thromboembolism Clinical Trials and Outcomes Research (CanVECTOR) network. FK is supported by a  Canada Graduate Scholarship  from the  Canadian Institutes of Health Research (CIHR) , and  Drug Safety  and  Effectiveness Cross-Disciplinary Training (DSECT) award  from the  CIHR. Contributors FK and MAR conceived the idea and design for this systematic review. FK, AR, BH, GW and MAR developed the methodology for the systematic review protocol. The contents of this manuscript were drafted by FK, AR, MC, BH and MAR with input from all members of the authorship team. The manuscript was reviewed by CK, SS, FC, PP, SE, CB, GA, HRB, TAB, GP, LP, ES and GAW for important intellectual content. All authors read and approved the final manuscript.
We explain in a unified way the experimental data on ultrahigh energy cosmic rays (UHECR) and neutrinos, using a single source class and obeying limits on the extragalactic diffuse gamma-ray background (EGRB). If UHECRs only interact hadronically with gas around their sources, the resulting diffuse CR flux can be matched well to the observed one, providing at the same time large neutrino fluxes. Since the required fraction of heavy nuclei is, however, rather large, air showers in the Earth's atmosphere induced by UHECRs with energies E > ∼ 3 × 10 18 eV would reach in such a case their maxima too high. Therefore additional photo-hadronic interactions of UHECRs close to the accelerator have to be present, in order to modify the nuclear composition of CRs in a relatively narrow energy interval.
Conclusions We studied in Ref. [1]  if a single source class can explain both the flux and the composition of extragalactic CRs including the sub-ankle region and the high-energy neutrinos observed by IceCube. Using only hadronic interactions of UHECRs with gas around their sources, we obtained a good fit to the CR energy spectrum, however, only if intermediate nuclei are sub-dominant. Therefore the predicted maximum X max of CR-induced air showers lies higher in the atmosphere than observed. Adding photo-nuclear interactions, with a relatively large interaction depth, we were able to reduce significantly the fraction of heavy nuclei in the primary fluxes and, consequently, to fit satisfactorily both the spectrum and the composition data on UHECRs. At the same time, the high-energy neutrino flux obtained matches IceCube measurements, while the contribution of unresolved UHECR sources to the EGRB is of order 30%.
Abstract. This study presents a comparison between the retrieval of optical properties of aerosol above clouds (AAC) from different techniques developed for the A-Train sensors CALIOP/CALIPSO and POLDER/PARASOL. The main objective is to analyse the consistency between the results derived from the active and the passive measurements. We compare the aerosol optical thickness (AOT) above optically thick clouds (cloud optical thickness (COT) larger than 3) and their Ångström exponent (AE). These parameters are retrieved with the CALIOP operational method, the POLDER operational polarization method and the CALIOP-based depolarization ratio method (DRM) -for which we also propose a calibrated version (denominated DRM SODA , where SODA is the Synergized Optical Depth of Aerosols). We analyse 6 months of data over three distinctive regions characterized by different types of aerosols and clouds.
From these products we used the AOTs retrieved at 532 and 1064 nm, the aerosol base and top altitudes, the cloud top altitude, the ice-water cloud phase and the feature type. We also use CALIOP level 1 dataset, labelled CAL_LID_L1-ValStage1 (link above), which provides the attenuated backscatter coefficient calculated at a vertical resolution of 30 m from -0. 5 to 8. 2 km altitude and at 333 m horizontal resolution  (Winker et al. , 2007).
The main uncertainties of the DRM Hu are linked to the calibration of the lidar, which impact the estimate of the parameters in Eq. (  5 ). Providing a robust, self-calibrated method at global scale and for the whole CALIPSO dataset is not trivial and, in order to improve the estimate of the AOT with the DR method, the developers of the Synergized Optical Depth of Aerosols and ICE clouds (SODA & ICE, available at the ICARE thematic centre),  Josset et al. (2010 Josset et al. ( , 2012)) , modified the original formalism of DRM Hu. The main reason for these modifications is that the relationship between the multiple scattering factor and the depolarization by the cloud shows a systematic deviation from the theory (see Fig. 2  in  Hu, 2007). The multiple scattering-depolarization relationship has been confirmed by laboratory experiments  (Cao et al.
5 years of data we considered in this study, the median of S c,lat for the nighttime data is 19. 36 sr, which is interestingly close from the theoretical value determined by  Hu et al. (2006). For daytime data, S c,lat is systematically higher and with a median of 20. 64 sr. The systematic daytime-nighttime difference could be geophysical. However, it is premature to reach such conclusion until all nighttime-daytime differences in the CALIPSO data have been addressed. Lastly, all these coefficients are finally integrated in the AOT retrieval equation: τ top,DRcalibr = - 1 2 ln 2S c,lat η calibr γ water,parallel , (10) Throughout this study, we will refer to this product as DRM SODA , which can be found at ICARE Data and Services Center (http://www. icare. univ-lille1. fr/projects/soda/).
Collocation The A-Train satellites pass through close orbits within several minutes, providing coincident observations of POLDER, MODIS and CALIOP instruments. Using the nearest pixel approximation, CALIOP files are used as a space reference for sampling POLDER and MODIS products. CALTRACK is the output dataset and can be found at ICARE. It contains coincident data from POLDER at 18 km × 18 km and MODIS, extracted under the CALIOP track at 5 km horizontal resolution. The DRM Hu and DRM SODA optical depth retrievals are processed at the CALIOP native resolution of 333 m and aggregated afterwards at 5 km horizontal resolution. Moreover, for a better consistency of the AOT comparison, the POLDER AOT was extrapolated at 532 nm using the AE retrieved with the POLDER algorithm. We also limited the cloud top altitude at 5 km because we are interested in low-level clouds.
Aerosol layers with the base altitude within a distance between 100 and 500 m above the cloud layer are considered too uncertain and are excluded from our study. We also removed the situations for which the detected CALIOP aerosol top and/or bottom altitudes are located below the cloud top, assuming that these data are highly uncertain. Practically, we rejected the CALIOP data for which the aerosol layer penetrates the cloud layer by more than 50 m. The third category, "undetermined", corresponds to situations for which the respective position of the aerosol or cloud layer is not identified by the CALIOP layer detection algorithm (i. e. missing data), even though POLDER and DRM AAC AOT retrievals are valid. We chose to keep these data in our analysis as they cover the majority of POLDER AAC detected cases with a non-negligible AOT (even if CALIOP classifies them as invalid or noise), as the purpose of the paper is to better understand the differences between the methods.
e. BBA and DDA). Overall, DRM SODA and DRM Hu give sim-ilar results. However, the AOTs retrieved with DRM Hu are generally larger than those of DRM SODA for all the three regions (i. e. 0. 37 compared to 0. 28 for SAO; see Table  4 ). While DRM SODA has a constant negative offset when compared to POLDER, DRM Hu rarely retrieves null AOT values (offsets always larger than 0; see Table  2 ). This is likely to be a consequence of the calibration performed for the DRM SODA method. Also, there is no obvious correlation between the CALIOP OM and POLDER AOT 532 nm retrievals for all regions. Finally, in addition to the 6-month regional study, we also examined the impact of the vertical aerosol-cloud profiles over the three regions using data acquired from May to October between 2006 and 2010. We systematically found higher correlation coefficients between the DRM SODA and POLDER AOTs when the layers were well separated than when they were in contact (see Table  6 ).
The AE given by both methods is approximately 1. 0 (when considering only AE values associated with AOT > 0. 1). The lateral histogram shows that the POLDER method identifies AAC events associated with both low and high AE values, resulting in a mean AE of about 1. 0. The undetermined situations correspond to retrievals when CALIOP does not give all the information regarding the layer altitudes. The number of cases is significant (approximately 92 % of the total number of global retrievals) but most of data (95 %) correspond to AOT 532 nm lower than 0. 2. This probably explains why the layer detection algorithm has difficulties in estimating the base and top of the aerosol layer. For the undetermined cases, we observe that there is not much correlation between POLDER and DRM SODA measurements.
Evolution of the above-cloud AOT retrievals with cloud properties In principle, the retrieval of AAC properties from the methods considered in this study should not depend on the properties of the underlying clouds. However, hypotheses and empirical relations used in the retrieval methods to exploit the signal backscattered by the underlying cloud cover obviously have their limitations. In order to understand potential issues linked with diversity of cloud properties, we analyse in this section the difference between the AOT retrievals of POLDER, DRM SODA and DRM Hu by classes of cloud properties (COT and r eff retrieved with MODIS). We considered global measurements acquired for 4. 5 years of data and used the classification defined in Sect. 2. 3. 2. Figure  6  presents POLDER and DRM SODA AOT 532 retrievals as a function of the MODIS droplets effective radius (r eff ), while Fig.
In order to understand how the vertical profiles differ from one situation to another, we compared the CALIOP attenuated backscatter coefficient for attached and detached cases. We considered the period 2006-2010 and used data acquired over the entire globe. We only select the attached and detached cases where the cloud top altitude is below 1. 5 km, the COT is larger than 5 and the DRM SODA AOT 532 nm is larger than 0. 1. These criteria allow for selection of data that correspond to AAC events associated with similar cloud vertical extents and with significant AOTs. For these cases, we computed the average and median of the CALIOP level 1 attenuated backscatter coefficients at 532 nm. Figure  10  presents these results and some information concerning the mean and median values of CALIOP level 2 products: cloud top altitude, aerosol layer's base and top altitudes.
Acknowledgements. Lucia Deaconu 's grant is provided by the  CaPPA project (Chemical and Physical Properties of the Atmosphere) , which is funded by the  French National Research Agency (ANR)  through the  PIA (Programme d'Investissement d'Avenir)  under contract  ANR-11-LABX-0005-01  and by the  Regional Council Hauts-de-France  and the  European Funds for Regional Economic Development (FEDER). Edited by: Piet Stammes Reviewed by:  Hiren Jethva  and two anonymous referees.
, 1992; Sanchez Goñi et al. , 2008) , they provide a suite of case studies that can be used to investigate the impact of abrupt climate change on terrestrial ecosystems. The ACER (Abrupt Climate change and Environmental Responses) project was launched in 2008 with the aim of creating a global database of pollen and charcoal records from the last glacial period (73-15 ka) which would allow us to reconstruct the regional vegetation and fire changes in response to glacial millennial-scale variability and evaluate the simulated regional climates resulting from freshwater changes under glacial conditions. Although there are 232 pollen records covering the last glacial period worldwide, only 93 have sufficient resolution and dating control to show millennial-scale variability  (Harrison and Sanchez Goñi, 2010).
It was necessary to reevaluate and harmonize the chronologies of these individual records to be able to compare patterns of change from different regions. In this paper, we present the ACER pollen and charcoal database, including the methodology used for chronological harmonization and explore the potential of this data set by comparing two harmonized pollen sequences with other palaeoclimatic records. Such a comparison illustrates the novel opportunities for the spatial analyses of the impacts of global climate events using this research tool.
Compilation of the records The ACER pollen and charcoal database includes records covering part of or all of the last glacial period with a sampling resolution from a few centuries to less than 1000 years, which allows the identification of centennial-scale vegetation changes similar in duration to the current global climate change. These records were collected as raw data, through direct contact with researchers or from the freely available European and African Pollen Databases. Four records were digitized from publications using the Grapher TM 12 (Golden Software, LLC) because the original data were either lost (Kalaloch:  Heusser, 1972 and Tagua Tagua: Heusser, 1990)  or are not publicly available (Lac du Bouchet:  Reille et al. , 1998 and Les Echets: de Beaulieu and Reille, 1984). These digitized records are available as pollen percentages rather than raw counts.
Harmonization of database chronologies The chronology of each of the records was originally built as a separate entity. In order to produce harmonized chronologies for the ACER database, decisions had to be made about the types of dates to use, the reference age for the "present" (b2k or the year 1950), the choice of calibration curve, the treatment of radiocarbon age reservoirs, and the software used for age-model construction. Radiometric ages ( 14 C, 235 U/ 230 Th, optically stimulated luminescence (OSL), 40 Ar/ 39 Ar) and radiometrically dated tephras are given preference in the construction of the age models. The tephra ages were obtained either through direct 40 Ar/ 39 Ar dating of the tephra or 14 C dating of adjacent organic material (Table  1 ). When a radiometric or tephra date was obtained on a unit of sediment, the depth of the midpoint of this unit was used for the date in the age modeling.
We used the IntCal13 and Marine13 calibration curves for terrestrial and marine 14 C dates, respectively  (Reimer et al. , 2013) , which are the calibration curves approved by the radiocarbon community  (Hajdas, 2014). Although studies have shown that the radiocarbon ages of tree rings from the Southern Hemisphere (SH) are ca. 40 years older than Northern Hemisphere (NH) trees formed at the same time  (Hogg et al. , 2013) , this difference is smaller than the laboratory errors on most of the 14 C dates, and, since the Marine13 calibration curve does not distinguish between SH and NH sites, we use the NH IntCal13 calibration curve for all the records. The Marine13 calibration curve includes a default 400year reservoir correction. We adjusted this correction factor for all the 26 marine records included in the database using the regional marine reservoir age ( R) in the Marine Reservoir Correction Database (http://calib.
Moreover, BACON and Bchron  (Haslett and Parnell, 2008; Parnell et al. , 2008)  do not handle sudden shifts in accumulation rate very well, and such shifts are not uncommon across deglaciation and stadial time periods. We therefore use the classical age-modeling approach in the CLAM software  (Blaauw, 2010) , implemented in R (R version 3. 3. 1) (R Development Core Team, 2016), to construct the age model. Several age models were built for each record using the calibrated distribution of the radiometric dates: (a) linear interpolation between dated levels; (b) linear or higher-order polynomial regression; and (c) cubic, smoothed or locally weighted splines (Supplement Table  S1 ). For general guidance, we have selected the age model that has goodness-of-fit values that are among the lowest but that are not necessarily the lowest (Supplement Table  S2 ).
The linear interpolation model was favored because it is generally the most parsimonious solution for records with no age reversals. For regression and spline models, the selection of the model was based on a combination of visual inspection and goodness-of-fit values; this allows the selection of the model including most of the outliers and realistic changes in sedimentation rates. If none of the regression or spline models provided a better fit, we built age models after excluding outliers proposed by the original authors (Supplement Table  S1 ). The database includes information on the single "best" age model and the 95 % confidence interval estimated from the 10 000 iterated age-depth models (weighted mean) for every sample depth.
The structure of the database The ACER pollen and charcoal data set is archived in a Microsoft Access TM relational database. There are six main tables (Fig. 1 ). 3. Pollen data. The pollen data are recorded as raw counts or as the pollen percentage of each pollen and spore morphotype identified. The table records the identification number of each sample (sample ID), the taxon name and count/percentage. The taxa names were standardized across cores with respect to the accepted use of terms such as type presented in different pollen determination key publications (e. g. ,  Moore et al. , 1991; Faegri et al. , 1989)  Dates that are based on recognized events are also listed and identified by the name of the event (event name) and the type of record in which it is detected (tracer used). The column "is_used" corresponds to the dates used by the authors for building the original age models.
6. ACER dating information. The ACER dating information table duplicates the original dating information file, except that it provides information about the explicit corrections and the harmonized control points used to produce the ACER age models (Table  1 ). Specifically, it gives the calibration curve used (no calibration, Int-Cal13, Marine13) and the local reservoir age (and uncertainty) for marine cores. The ACER database allows archiving multiple cores retrieved at the same site (site name followed by the name of the core). In such a case, an age-depth model is constructed for each core and archived in the database. Additional tables document the codes used in the main tables for, e. g. , basin type, basin size, date type, material dated, calibration curve and biome percentage table, which includes selected biomes provided by the authors (Table  2 ).
The taxa defining the pollen percentages of the main forest biomes are those originally published by the authors in the Quaternary Science Reviews special issue  (Fletcher et al. , 2010; Hessler et al. , 2010; Jimenez-Moreno et al. , 2010; Takahara et al. , 2010). The taxa defining the pollen percentages of the main biomes from Africa (sites Mfabeni and Rumuiku) Australia (sites Caledonia Fen and Wangoom) and New Zealand (site Kohuora) not included in this issue are described in the Supplement. Each table of the ACCESS database is also available as. csv file: (a) site, (b) sample (original depth-age model and ACER depth-age model), (c) dating info (original dating information), (d) dating info ACER (harmonized dating information from this work), (e) pollen data (raw data or digitized pollen percentages; pollen percentages of different biomes) (Table  2 ), (f) unique taxa in database (list of all the identified taxa) and (g) charcoal data (raw or digitized).
The ACER pollen and charcoal database ACER database comprises all available pollen and charcoal records covering all or part of the last glacial period (73 to 15 ka) as of July 2015. It contains 93 well-resolved pollen records (< 1000 years between samples), 32 of which include charcoal data, from all the major potential present-day biomes (Fig. 2 ). There are 2486 unique pollen and spore taxa in the database. Harmonized age models were constructed for 86 out of the 93 records (Supplement Table  S2 ). The seven sites without harmonized age models are F2-92-P29 (no radiocarbon age errors available), Bear Lake (pollen was counted on one core but sample depths could not be correlated with the cores used for dating), EW-9504 and ODP 1234 (original age models based on correlation with another core, but tie point information was not available), Okarito Pakihi (no dating information available) and Wonderkrater borehole 3 (multiple age reversals).