dataesr/scientific-paragraphs-categorization huggingface dataset:
Combined dataset The combined dataset includes the new dataset and the published dataset  (Aggarwal et al. , 2014). Dermal absorption values from liquid concentrates were 0. 6, 1. 3 and 5. 2% at median, 75th and 95th percentiles, respectively while corresponding values from solid concentrates were 0. 3, 0. 7, and 1. 6% (Fig. 2A , Table  2 ). As for the previous and the new dataset, the combined dataset shows higher absorption values for liquid concentrates compared to solids, especially at the 95th percentile, therefore, separate defaults of 6% and 2% are proposed for liquids and solids, respectively. Dermal absorption values from spray dilutions of liquids or solids were 7. 2, 15. 8 and 29. 9% or 4. 6, 9. 4 and 27. 8% at median, 75th and 95th percentiles, respectively (Fig. 2B, Table 2 ).
Consistent with the individual datasets, the combined dataset also showed similar dermal absorption values from spray dilutions of liquids and solids. Therefore, the data were combined and resulted in values of 6. 7, 15. 5 and 31. 9% for median, 75th and 95th percentiles, respectively (Fig. 2B , Table  2 ). Although, the 95th percentile value for all dilutions in the combined data set was 31. 9%, a single pragmatic default of 30% (which is actually the 94th percentile) is proposed for all dilutions.
Effect of active substance loading on default values for concentrates EFSA GD (2012) has 2 different defaults for concentrates (75% for concentrations < 5%; otherwise 25%), Therefore, current data were analysed to see whether active substance loading in the formulation influenced dermal absorption. The influence of concentration on dermal absorption is presented in Fig. 3 , where datasets (new or combined) are divided into two groups -one group where active substance concentrate is <5% and the other with P5% loading. Contrary to EFSA guidance, dermal absorption from concentrates was not influenced by concentration (Fig. 3A  and B ). The data indicate that two different defaults for concentrates based on active substance content are not justified.
New dataset Dermal absorption values from individual formulation types and groupings of formulations are presented in Figs. 4A  and 5A ,   respectively. At 95th percentiles, EC, SE and SL types have slightly higher absorption than other types of formulation, though replicate (n) for SL types is low compared to EC and SE types of formulations. However, a greater difference in dermal absorption is seen between organic-solvent based versus primarily water based/dispersed formulation or solids (Fig. 5A ). ANOVA found a pronounce statistically significant effect of grouping on dermal absorption (F(2,167) = 18. 18, p ( 0. 01, r = 0. 41). Tukey-HSD post hoc analysis (comparing log-means and not percentiles) revealed significant group differences between organic-solvent based and both primarily water based (p ( 0.
Combined dataset Dermal absorption values from individual formulation types and groupings of formulations are presented in Figs. 4B  and 5B , respectively. At 95th percentiles, EC, SE and SL formulations had similar dermal absorption values though 'n' for SL was low (n = 14; Fig. 5B ). Consistent with the new dataset (data not presented as n was <5) and previous data  (Aggarwal et al. , 2014) , EW formulations had relatively higher dermal absorption (approximately 10%) but 'n' was small (n = 10; Fig. 4B ). As with the new dataset, the combined dataset also showed considerably higher dermal absorption from organic-solvent based formulations compared to primarily water based/dispersed or solid formulations (Fig. 5B ). However, a strong difference was not observed between primarily water based/dispersed versus solid formulations (Fig.
Effect of concentration on dermal absorption from spray dilutions EFSA GD (2012) requires linear extrapolation (i. e. , pro rata correction) between dermal absorption and concentration in a spray dilution. Therefore, current data were analysed to see whether spray dilution concentration influenced dermal absorption. The effect of spray dilution concentration on dermal absorption is presented in Figs. 6  and 7  for both new and combined datasets. Fig. 6  presents the impact of concentration in 10-fold ranges e. g. , 10-1, 1-0. 1, etc. on dermal absorption. As two spray dilutions were tested in most studies, the impact of change in concentration was plotted against the fold change in dermal absorption (Fig. 7 ).
New dataset At 95th percentiles, there was no difference in dermal absorption between spray dilution ranges of 10-1 versus 1-0. 1 versus 0. 1-0. 01 g/L (Fig. 6A ). At medians or 75th percentiles, except for highly diluted sprays (range 0. 01-0. 00075 g/L), there was an increase (though non-linear) in dermal absorption from highly concentrated spray dilutions (10-187. 5 g/L) to less concentrated dilutions (0. 01-0. 1 g/L). There is a pronounced drop in dermal absorption at the lowest concentration range but 'n' is only 2 (Fig. 6A ). In the new dataset, there were 93 studies in which two spray dilutions were tested. As seen graphically (Fig. 7A ) this assessment showed no linear correlation between change in spray concentration and dermal absorption. The absence of correlation (regression coefficient 28%) is further confirmed by a line of best fit (polynomial regression: F(5,89) = 8.
Combined dataset Similar results to the new dataset were seen with the combined dataset (Fig. 7B ). In the combined dataset the regression coefficient was 48%, which confirms the lack of a linear relationship between dermal absorption and dilution factor. Only 8 of 136 values exceeded a 5-fold increase in dermal absorption; these 8 values were 5. 2, 5. 7, 5. 8, 6. 7, 9. 4, 13, 14. 5 and 45. 6 from 7. 2-, 108-, 20. 4-, 15. 6-, 13. 8-, 16. 2-, 66. 7-and 138. 5-fold increases in dilution factor, respectively. However, interestingly, the 95th percentile of all dermal absorption foldchange increases is 5. 3, which adds further support to a proposed default limit of a 5-fold increase in dermal absorption. Overall, the combined dataset suggests (1) no linear relationship between dilution factor and dermal absorption beyond 5-fold increases in dilution, (2) the increase in dermal absorption was typically less than 5-fold.
Relationship between MW or Log P ow and dermal absorption EFSA Guidance (2012) proposes use of a 10% dermal absorption default value for an active substance with MW >500 g/mol and Log P ow <À1 or >4. 3. Out of 108 active substances in this dataset only 3 (2. 8%) meet these criteria. In these 3 studies, dermal absorption values were 0. 6%, 0. 8% and 1. 0% from the concentrates and 3. 8%, 4. 6% and 5. 7% from the spray dilutions. Graphical analysis (Fig. 8 ) does not reveal a relationship between MW or Log P ow and dermal absorption.
Basing dermal absorption default values on percentiles of datasets Dermal absorption is an input parameter in EU regulatory Tier 1 models used to estimate human exposure to active substances for operators, bystanders, residents and re-entry workers. EFSA's proposed default dermal absorption values are based on maximum values from their dataset. The use of maximum values is a highly conservative option, which is not consistent with human exposure models and also effectively ignores all other values in the dataset. It is also interesting to note that the studies used to derive the maximum values are questioned in the EFSA Scientific Opinion (2011) itself: for the 5 active substances with the highest dermal absorption values for concentrates (18-26%, mainly in rats), EFSA acknowledged that ''if well performed human in vitro studies had been available on these products as concentrates, dermal absorption values lower than those derived by PRAPeR would probably have been obtained''.
For dilutions, the EFSA dataset contained only 5 values higher than 30%, and these studies were considered of questionable quality. The current regulatory proposal for non-dietary human exposure assessments is to use descriptive statistics of the assessed data packages, e. g. , the 75th percentile of the exposure data distribution for sub-chronic exposure scenarios, which has been accepted in the EU for decades, and the 95th percentile for acute exposures  (EFSA, 2010 (EFSA, , 2014)). The 'German model' for operator exposure assessment (BBA, 1992) uses geometric means to provide better control of outliers compared to 75th percentiles. From a scientific perspective, it would be logical to align default dermal absorption values with the corresponding EFSA human exposure defaults by using the 75th and 95th percentile values for short-term and acute scenarios, respectively.
Dermal absorption definitions and residue in skin Regarding dermal absorption definitions, OECD considers an absorbed dose as the ''mass of test substance reaching the receptor fluid or systemic circulation within a specified period of time''  (OECD 428, 2004). This OECD definition is supported by a recent review that compared 92 datasets of human in vivo and in vitro dermal absorption data  (Lehman et al. , 2011). When the absorbed dose in human volunteers was compared to corresponding receptor fluid values from in vitro studies with human skin, the mean in vitro to in vivo ratio for the entire dataset was 1. 6, and for the eleven harmonised studies, the correlation was almost perfect (0. 96). For regulatory purposes, it would be reasonable and conservative to assume the in vitro residue in the vascular dermis as absorbed, even though it had not diffused into the receptor fluid by the end of a 24-h experimental period.
This option would provide the most relevant value for use in risk assessments for PPP, while still remaining acceptably conservative. That said, for expediency and to increase the opportunity for refinement of current regulatory criteria  (EFSA, 2012)  this review adopted the most conservative approach of using EFSA's worstcase definition: Dermal absorption = [Radioactivity present in receptor fluid + receptor chamber wash + whole skin sample] À [radioactivity in the first two tape strips]. An initial assessment (data not presented) of the new and combined dataset indicated that approximately half of the resulting dermal absorption values derived by this method have more than 50% of the 'absorbed dose' in the skin at the end of the experimental period. Interestingly, those compounds showing high skin residues and thus impacting the dermal absorption estimates according to EFSA's worst-case definition coincide with low penetrations into the receptor compartment (data not shown).
Defaults for concentrates 303 dermal absorption values for concentrates were assessed (Figure  2A , Table  2 ). As all studies in this review were OECD GLP and test guideline-compliant, of one type and the number of observations was very high in comparison with the EFSA dataset (Table  4 ) they are considered to be sufficiently robust to derive reliable and definitive conclusions. Results show that dermal absorption from liquid concentrates was, as expected, higher than solid concentrates. Therefore, two different default values are proposed for concentrates: 6% for liquid and 2% for solid concentrates. These defaults are in agreement with previously proposed values  (Aggarwal et al. , 2014). 4. 2. 1. 1. Impact of active substance concentration on dermal absorption. EFSA guidance contains two different default values for concentrates depending on concentration of the active substance in the concentrate.
Default values for spray dilutions 446 dermal absorption values for a broad range of dilutions were assessed (Figs. 1D  and 2B ; Table  2 ). Dermal absorption from dilutions of liquids and solids were similar and support a single default value. The 95th percentile of all dilutions (n = 446) was 31. 9%. As described in Section 3. 1, some of the highest dermal absorption values appeared to be outliers but a definitive rationale for exclusion could not be established. As a precautionary approach, these values were retained, but if they had been excluded, the 95th percentile would have been 30%, which actually represents the 94th percentile of the combined dataset. Therefore, a reasonable and pragmatic default of 30% is proposed for all dilutions, which is in line with the previous assessment  (Aggarwal et al.
Impact of dilution on dermal absorption In a gross analysis, dermal absorption was low for both extremes of spray concentrations (>10 or <0. 01 g/L) however, at concentration between 10 to 0. 01 g/L, absorption was stable at 95th percentile or median levels but a non-linearly increasing trend was apparent for the 75th percentiles  (Fig 6). Therefore, a higher-tier analysis was performed for studies where two spray dilutions were tested (134 studies; Fig. 7B ). Results showed dermal absorption increased with dilution but not in a linear fashion. For the combined dataset, the 95th percentile of fold-increase in dermal absorption with fold-increase in dilution was 5. 3, and except for 8 of 134 studies the increase in dermal absorption was <5 irrespective of fold change in dilution (Section 3.
When these values were excluded from the model fit based on their Cook's distance  (Cook, 1977)  the regression coefficient dropped to 0. 16. When a similar approach was applied to the new dataset, three influential observations were identified, one WP formulation with a dilution factor of 67 and absorption fold change of 14 and two SL formulations with dilution factors of 630 and 650 and fold changes of 3. Excluding those values from the model for the new data resulted in a coefficient of determination of 0. 19, low and comparable to the previous dataset. When those studies are excluded from the fit of the combined dataset, the regression coefficient was reduced to 0. 39. The regression coefficient values for simple linear regressions are even lower; hence no linear dose-response relationship could be statistically established for dermal absorption fold change and dilution factor.
Relationship between MW or Log P ow and dermal absorption EFSA guidance (EFSA, 2012) proposed use of a 10% dermal absorption default value for an active substance with MW >500 and Log P ow <À1 or >+4 (Table  2 ). In the current dataset (Fig. 8 ) only 3 of 108 active substances met these physico-chemical criteria, and dermal absorption was <1% and <6% for concentrates and spray dilutions, respectively. Therefore, a separate default value for concentrates based on MW or Log P ow is not required.
Conclusions This analysis was carried out using a combination of the EFSA worst-case option for dermal absorption (i. e. , skin residue except first 2 tape strips is absorbed) and 95th percentile values of the datasets. The analysis supported (1) defaults of 6% for liquid and 2% for solid concentrates irrespective of the active substance loading, (2) a single default of 30% for all spray dilutions irrespective of formulation type, (3) solvent-based formulations (EC type) as conservative surrogates for read-across for primarily water based/dispersed and solid formulations, similarly, dermal absorption values derived from primarily water-based/dispersed formulations can be used as a read-across for solids, (4) absorption not increasing linearly with dilution; rather there should be no adjustment for a <2-fold change, a linear increase between 2 to 5-fold or use of a default of 30% and (5) stratum corneum not being considered part of an absorbed dose.
Conflict of interest statement A. H. and F. M. K. worked as paid consultants for ECPA and complied and collated the dataset, generated the figures and tables and conducted the statistical analysis of the data. Additionally they supported M. A. in developing the manuscript. All other authors are employees of the companies that own the dataset. They are scientists and experts in the field of dermal absorption or regulatory toxicology. They actively participated in the data collation and evaluation, and preparation and review of this article.
The overall overestimation is less pronounced for ERA-Interim because the overestimation observed in clear sky conditions is counter-balanced by underestimation in cloudy conditions. The squared correlation coefficient for clearness index ranges between 0. 38 and 0. 53, showing that a very large part of the variability in irradiation is not captured by the re-analyses. Within an irradiation homogeneous area, the variability of the bias, root mean square error and correlation coefficient are surprisingly large. MERRA and ERA-Interim should only be used in solar energy with proper understanding of the limitations and uncertainties. In regions where clouds are rare, e. g. North Africa, MERRA or ERA-Interim may be used to provide a gross estimate of monthly or yearly irradiation. Satellite-derived data sets offer less uncertainty and should be preferred.
Re-analysis estimates should not be mistaken with observed data in SSI because while the re-analysis method assimilates state variables such as temperature, moisture and wind, physics variables such as radiation and cloud properties derive from a model and include the uncertainty of this model. However, because of the advantages listed above in coverage, availability and costs, re-analyses are appealing to companies and several are using re-analyses in their daily work. This paper aims at establishing the quality of re-analyses when compared to qualified ground measurements. Ref. [15]  published a similar work using the MERRA re-analysis in order to estimate the climatological variability of the photovoltaic power production over Czech Republic. Our study complements their work and other similar studies in meteorology for limited areas and adds more evidence by comparing MERRA re-analyses to a large number of ground stations located in Europe, Africa and Atlantic Ocean.
The limitation in geographical coverage of the present study is explained by the expertise of the authors who are dealing with this area for long. In addition, our study reports on the ERA-Interim re-analysis. To better apprehend the possible benefits of re-analyses, a comparison is also performed with the database HelioClim-1 of daily irradiation created by MINES ParisTech within the HelioClim project  [3]  and extensively validated against ground measurements. HelioClim-1 is a well-known database of easy access on the Web at no cost with many usages and approximately 400 requests per working day  [17]. It will be seen whether the re-analyses offer better accuracy than HelioClim-1. Refs. [4, 24]  have compared measurements made at several ground stations located in the same area: Mozambique, to HelioClim-1 and have found that though Mozambique is fairly homogeneous regarding SSI, the differences between HelioClim-1 and ground measurements are spatially variable.
MERRA re-analysis The MERRA data set  [22]  has a resolution of 0. 5 Â 0. 65 with 72 vertical levels from ground to 0. 01 hPa. The radiative transfer model for shortwave radiation (CLIRAD-SW) is described in Ref. [9]. MERRA includes an odd-oxygen family transport model providing the ozone concentration necessary for solar absorption. Production and loss of ozone as well as other optically active species are specified from climatology of the Goddard two-dimensional chemistry and transport model  [12]. The hourly SSI estimates are horizontally interpolated using a bilinear interpolation technique, to the measurement site from the closest four surrounding grid cells with a weighting factor that is inversely proportional to the distance. Daily irradiation is computed by summing the hourly SSI estimates after multiplying them by the number of seconds in 1 h.
ERA-interim re-analysis The ERA-Interim data set  [11]  has a resolution of 0. 75 Â 0. 75 and counts 60 vertical levels from ground to 0. 1 hPa. Ref. [11]  noted an overestimation of 2 W m À2 of the incoming radiation at the top of the atmosphere. The radiative transfer model uses the prognostic water vapour and cloud variables (cloud cover, cloud condensed water) from the meteorological model and climatologic values for aerosols, carbon dioxide, trace gases and ozone. The SSI is estimated every 3 h. Similarly to MERRA, the SSI is bi-linearly interpolated to the measurement site. Daily irradiation is computed by summing the eight available SSI estimates after multiplying them by the number of seconds in 3 h.
HelioClim-1 database The HelioClim Project is an ambitious initiative of MINES Par-isTech launched in 1997 after preliminary works in 80's  [3]  to increase knowledge on the SSI and to offer SSI values for any site, any instant over a large geographical area and long period of time, to a wide audience. The project comprises several databases that cover Europe, Africa and the Atlantic Ocean. These databases use satellite images as inputs for their creation and updating. The HelioClim-1 database offers daily means of the SSI for the period 1985e2005. The accuracy of the HelioClim-1 data has been assessed by comparison with ground measurements made by high-quality pyranometers on a daily basis. If well-calibrated and wellmaintained, these pyranometers exhibit a relative uncertainty of 10% of the daily mean of SSI at a 95 per cent confidence level  [27].
Ref. [18]  compared 55 sites in Europe for the period June 1994eJuly 1995 and 35 sites in Africa for the period 1994e1997. Ref. [1]  compared HelioClim-1 data with ground measurements in Algeria, Egypt, and Tunisia. Refs. [4, 24]  performed a similar study for Mozambique, while Ref. [20]  focused on Southern Africa. These works demonstrated that the HelioClim-1 database offers good quality for Africa, the Mediterranean Basin, and more generally for latitudes comprised between À45 and þ45. Outside these limits, the quality may decrease because of the characteristics of the satellite images used for the construction of HelioClim-1  [3]  though this is not a systematic effect and local conditions may prevail. The HelioClim-1 has many usages as illustrated by published works in various domains: oceanography, climate, energy production, life cycle analysis, agriculture, ecology, human health, and air quality  [17].
The Global Earth Observation System of Systems (GEOSS) is a project aiming at proactively linking together existing and planned observing systems around the world and supporting the development of new systems where gaps currently exist. The GEOSS Data-CORE (GEOSS Data Collection of Open Resources for Everyone) is a distributed pool of documented data sets with full, open and unrestricted access at no more than the cost of reproduction and distribution. The HelioClim-1 database has been identified as a Data-CORE by the GEOSS in November 2011  [14]. Previously, HelioClim-1 was open to researchers and students at no cost on a case-by-case basis. HelioClim-1 can easily be accessed at no cost on the Web (www. soda-is. com).
Ground measurements National meteorological services (NMS) usually measure solar radiation at a few sites. Data are sent to the World Radiation Data Center (WRDC), a laboratory of the Voeikov Main Geophysical Observatory in Saint-Petersburg, Russia, under the control of the World Meteorological Organization (WMO). There, the data are archived and published. They are available only for research and educational communities of the countries participating to WMO for non-commercial activities. Quality of measurement is difficult to assess from the WRDC archives. All data are scrutinized at WRDC and quality-flagged before entering archives. No information on uncertainty other than the flag is provided with the radiation data. It is considered that these data meet the requirements set by WMO for international exchange: relative uncertainty is 5%e10% for good to moderate quality  [27].