dataesr/scientific-paragraphs-categorization huggingface dataset:
Remote Sensing Data Data Acquisition and Preprocessing The Sentinel-2 Multispectral Imager is a European Space Agency (ESA) satellite for Earth observation that provides imagery with 13 spectral bands from the near-infrared (NIR) to short-wave infrared (SWIR). The radiometric images are provided with a range of spatial resolutions of 10 m, 20 m and 60 m (Table  1 ). Each Sentinel-2A or -2B satellite revisits the same area every 10 days (5 days with the twin satellites together). Images containing the study vineyard blocks (Section 2. 4. 3) were selected and processed via the Google Earth Engine (GEE) platform that enables large-scale processing of Sentinel-2 L2A (Sentinel-2A and Sentinel-2B) products. The time period considered for the study was from 13th May to 20th August 2019, which is the most relevant period to monitor vine growth vegetation in this region  [36].
Following Hollstein et al. [37] , decision trees and Bayesian models for cloud detection were applied to the Sentinel-2 images via GEE Javascript API to leave them in ready-to-use formats. Considering the revisit period of the Sentinel-2 (A/B) satellites, 25 images should have been potentially available over each block for the chosen time period. However, after cloud detection, the number of available images for each vineyard was 11 on average, with a range from 7 to 16 images depending on the location of the various vineyards. By using the GEE cloud-based platform to select Sentinel-2 images and pre-process them, the output was a file containing the spectral band values for each date (available images) and for each vineyard block.
Ground-Truth Data The ground-truth data were obtained from 107 vineyard blocks in the Languedoc-Roussillon region (Figure  3 ). These were all commercial productive blocks with characteristics representative of the Languedoc-Roussillon wine region in terms of plantation density, management practices and diversity of varieties. All blocks were non-irrigated. These blocks were selected because they all showed some effect related to the heat wave, such as stalled development, leaf burn and leaf drop. The severity of this effect on each of the 107 vineyard blocks was assessed locally by the winegrowers and advisors. Severity was evaluated several weeks after by an estimation of percentage yield loss. There was an acknowledgement that it was sometimes difficult to attribute the losses to the heat alone.
It is essential to place the results presented in this paper within the reality of multitemporal satellite data. Satellite observations are heavily conditioned by cloud coverage over the acquisition period. Despite this, this method was able to manage a time-series dataset with different sets of missing values by means of an interpolation on a date grid that was regularly spaced and optimised over the period of interest. The N-PLS methodology does not handle a high percentage of missing values within its cubic data structure and, it is expected that this approach would be affected in cases where cloud conditions during the target period significantly limit the number of available images. Another constraint that the model was able to deal with was the low number of ground truth samples (in this case, yield loss observations for grape fields).
It also can be difficult to directly compare and appropriately interpret data produced by multiple laboratories that are reduced and presented in different ways, especially when the data reduction choices made and the basis of the uncertainties presented are not always clear. Limited consensus on reporting formats has hindered the development and use of online databases for (U-Th)/He results, although such metadata archiving is an emerging requirement of journals and funding agencies to facilitate integration with other data sets and maximize the long-term impact and accessibility of data. Moreover, although He diffusion stepped-heating data comprise the foundation of the kinetic models that are used to interpret (U-Th)/He thermochronologic results, here again there are no universally adopted reporting approaches.
Overview A mineral's He diffusion kinetics determine its temperature sensitivity range and thus its utility for addressing different geologic problems. High-resolution interpretation of (U-Th)/He thermochronologic data depends on an accurate understanding of how He mobility varies as a function of temperature and other factors in the minerals dated. It also relies, to a large degree, on the observation that the fundamental control on the migration and loss of He through and from crystals follows thermally activated volume diffusion, where He atoms can be treated as interstitial impurities within a crystal lattice. He atoms located at various sites can randomly access neighboring sites at a rate that depends on the energy needed to jump between sites. The energy needed for jumping is determined by the nature of the mineral lattice.
g. ,  McDougall and Harrison, 1999 ). E a represents the exponential temperature dependence of diffusion, whereas D 0 or D 0 /a 2 can be thought of as the rate of diffusion at infinite temperature. Both of these kinetic parameters may be anisotropic within minerals. For example, for typical zircon and rutile compositions without substantial radiation damage, He diffusion is anisotropic (e. g. ,  Reich et al. , 2007; Farley, 2007; Cherniak et al. , 2009; Cherniak and Watson, 2011; Guenthner et al. , 2013; Anderson et al. , 2020). In contrast, in apatite and titanite, He diffusion is isotropic (e. g. ,  Reiners and Farley, 1999; Farley, 2000; Cherniak and Watson, 2011). Here, we briefly describe the factors that influence diffusional loss of He and how they can contribute to date variation. How He diffusion kinetics are measured, and associated considerations for reporting those data and their uncertainties, are described in section 8.
g. ,  Garver and Kamp, 2002; Ault et al. , 2018;  unfortunately, unlike zircon, color/opacity can't be used as a measure of radiation damage for typical apatite crystals). It can be advantageous to select a zircon suite with a wide range of radiation damage to obtain additional thermal history information from a zircon (U-Th)/He data set, although it may be problematic to interpret very high-damage zircon data with current kinetic models (sections 3. 3 and 4. 2). In some cases, additional tools are used to assist with selecting the optimal material for analysis. Besides petrographic microscopy, these may include examination by cathodoluminescence and backscatter images or fission-track maps (e. g. ,  Danišík et al. , 2010; Johnson et al. , 2017; Barham et al. , 2019) , LA-ICP-MS constraints on parent-isotope zonation (e.
g. , isotope dilution). □ Secondary mineral standards used for quality control (e. g. , Durango apatite, Fish Canyon Tuff zircon). □ Name(s) of lab(s) where data were acquired. troscopy spot analyses or maps bearing on the magnitude and/or heterogeneity of intracrystalline radiation damage (e. g. ,  Hardie et al. , 2017; Danišík et al. , 2017a; Anderson et al. , 2020). After selection, each grain is photographed, the crystal dimensions are measured, and the shape is characterized. Grains are typically measured using 2-D microscopy images and associated information is recorded, including the mineral length, width, number of terminations, grain geometry, and whether the grain is a whole crystal or a fragment. It is best to capture more than one 2-D image in order to measure not just grain length but also both minor axes, since assuming symmetry can lead to inaccuracies-for example, apatite grains may be somewhat flattened in shape.
He Measurement The next step in the data acquisition process is to determine the absolute amount of the daughter ( 4 He) in the crystal. The most common 4 He analysis protocol is for each selected crystal in its metal packet to be loaded into an ultra-high vacuum noble gas extraction and analysis line and degassed via heating by laser or furnace. The metal packet creates an evenly heated "microfurnace" during lasing and reduces parent nuclide volatilization that can occur during direct crystal heating  (House et al. , 2000). The sample is heated sufficiently to outgas all 4 He within several minutes, taking care not to reach extreme temperatures that can cause volatilization of parent nuclides. Typical temperatures may be ∼1000 °C for apatite and as much as ∼1350 °C for zircon, which can be quite retentive of some gas.
g. , standard crushing and grinding, SelFrag), water table, heavy liquids, drying temperature, and magnetic separation, as well as any pre-concentration techniques for detrital samples or chemical cleaning procedures. Mineral selection procedures include the method (microscopy and magnification used, any additional tools) and the criteria used for crystal selection (e. g. , size, morphology, clarity, color, lack of mineral and fluid inclusions, etc. ). Analytical procedures include the methods for He measurements (e. g. , instrumentation, laser or furnace heating, type of He analysis), the methods for crystal dissolution and U, Th, and Sm measurements (e. g. , dissolution protocol, instrumentation used, type of analysis), the mineral standards used for quality control, as well as the lab(s) where the data were acquired.
Mass dim -mass calculated from measured grain dimensions. Mass stoich -mass calculated using stoichiometric approach. relevant Ca and Zr isotopic data also comprise primary measured data. The absolute amount of daughter (He) is required to calculate He concentrations as well as uncorrected and corrected dates. The absolute amounts of parent (U, Th, and in some cases Sm) are required to calculate the F T factor, parent and eU concentrations, and uncorrected and corrected (U-Th)/He dates. Sm is measured for minerals with sufficient Sm to affect the date (typically apatite and titanite, but not zircon).
Minimum Needed Reporting Minimum needed data include the primary measured results that are needed to reproduce derived values. The core objective of reporting the measured data is to allow them to be reduced again in the future, which is important for the longer-term development of the technique as new discoveries about systematics are made and new statistical treatments are developed. The data measured thus also constitute the basic information necessary for inclusion in any database of (U-Th)/He data. In addition, as described more fully below, five main types of derived data should be reported (combined F T value, equivalent spherical radius, crystal mass, uncorrected date, and corrected date if considered appropriate). The various choices (e. g. , grain geometry calculation methods) made to compute the derived from the measured data should also be described.
Crystal dimension and stoichiometric (if acquired) data. Reported crystal dimension data should include the length and width(s) (typically in μm), the number of terminations, grain shape (e. g. , hexagonal prism, tetrahedral prism, ellipsoid), and whether the grain is a whole crystal or a fragment. The goal is to report all of the measurement data needed for volume and surface area estimates and therefore for calculation of F T values, equivalent spherical radius, mass, concentrations, and corrected (U-Th)/He date. If crystal mass is estimated stoichiometrically from Ca and Zr data rather than from the crystal dimensions, then these isotopic data should also be reported. Daughter (He) absolute amount. For each aliquot, the absolute amount of 4 He should be reported, generally in nmol, ncc at standard temperature and pressure (STP), or atoms.
Overview Interpretation of (U-Th)/He data acquired via the whole-crystal methods of analysis discussed above depends on knowledge of diffusion kinetics and diffusion behavior in the materials of interest. There are also other analytical methods that can shed light on the diffusion process that are likely to see increased use in the near future. Here, we first describe how He diffusion kinetic data are obtained and the types of Arrhenius relationships that are observed for minerals with single diffusion domain behavior (section 8. 2). Such data are typically acquired by laboratory diffusion experiments using either natural 4 He or proton-spallation-induced 3 He, although the CRH method also yields data from which kinetic parameters can be derived. We then discuss the 4 He/ 3 He method, which can not only be used to constrain kinetics (section 8.
Fundamentals and Measurement Methods Determining thermal histories is the goal of most (U-Th)/He mineral analyses, and given the significant mobility of He, even in geochronological applications it is important to assess whether the mineral has behaved as a closed system. As such, accurate knowledge of He diffusion kinetics is an essential underpinning of (U-Th)/He dating. As discussed in section 3. 1, the Arrhenius parameters D 0 and E a are key values that must be known when interpreting results from a mineral analysis. D 0 (or D 0 /a 2 ) and E a are most commonly determined using fractional degassing of He during laboratory stepped-heating diffusion experiments. Figure  9  illustrates the path from measured data to derived kinetic data for such experiments, and they are the focus of our reporting recommendations (Fig.
Data reduction is much easier if the measured isotope has a uniform distribution at the start of the experiment (without diffusion gradients, alpha-ejection profiles, or variations due to parent isotope zoning). The amount of He released at each step relative to the total amount of He in the sample yields fractional degassing information that can be converted to diffusivities using a set of simple equations (Fig. 9 ; e. g. ,  Fechtig and Kalbitzer, 1966; or McDougall and Harrison, 1999). These diffusivities are then plotted as ln(D/a 2 ) versus 1/T on an Arrhenius diagram, and these data are linearly regressed to calculate D 0 and E a (Figs. 9 and 10D; see next subsection). Diffusivity data are obtained using an assumed diffusion geometry (e. g. , sphere, infinite slab, infinite cylinder), so it is critical that all subsequent calculations use this same assumed geometry.
2. 4). The recently developed CRH approach  (Idleman et al. , 2018)  generates data that can be treated the same as stepped-heating analysis in obtaining kinetic parameters. Natural, empirical calibration experiments, in which (U-Th)/He dates for different minerals from the same rock sample are compared, are also important for evaluating the overall validity of diffusion kinetics inferred from experimental studies. The number of kinetics studies is relatively few, and there has been no community agreement to use a particular primary kinetic calibration. As such, no formal database has been established for noble gas kinetic data. Current practice is to make use of primary kinetic information embedded into current versions of thermal history modeling software, which generally use more evolved kinetic models that incorporate the primary data, and this represents a de facto consensus by the thermochronological community.
To give a concrete example, the RDAAM model for apatite published by  Flowers et al. (2009)  accounts for not only core diffusion kinetics but also the impacts of temperature-sensitive radiation damage; RDAAM is calibrated against published studies of He diffusion in various apatite crystals (e. g. ,  Shuster et al. , 2006). In turn, the RDAAM model is incorporated as one of several options in thermal history modeling software packages like HeFTy  (Ketcham, 2005)  and QTQt (Gallagher, 2012) (see companion paper,  Flowers et al. , 2022). In addition, other radiation damage models for apatite by  Gautheron et al. (2009)  and  Gerin et al. (2017)  are incorporated in QTQt. An issue that arises is that this approach treats all grains as identical in their kinetics, with radiation damage effects and grain size being the only control.
Arrhenius plots are also subject to artifacts as follows. If proton-induced 3 He is used for kinetic analysis, determining an Arrhenius relationship is fairly straightforward because it is a reasonable expectation that the initial distribution of 3 He is uniform, a key assumption made in the equations for obtaining values of D from fractional loss (Fig. 10A ). However, if 4 He is used, then for whole crystals the Arrhenius data may be complicated by non-uniform concentration profiles caused by some combination of alpha ejection, diffusional rounding, and intracrystalline zonation in U-Th (Fig. 10A ; e. g. ,  Goldsmith et al. , 2020). Both alpha-ejection and diffusional rounding deplete 4 He in the outer portion of the crystal. This produces a 4 He concentration profile that generates an Arrhenius array that is concave-up early in release and that only slowly approaches the expected linear array; the degree to which this occurs depends on the degree of rounding of the starting concentration profile relative to the flat profile that diffusion calculations expect (e.
g. ,  Goldsmith et al. , 2020). In addition, when modeling low-temperature Arrhenius data, both analytical infinite-series equations as well as finite-difference code have difficulty with accurately predicting very small fractional losses, requiring either a very large number of terms or very fine grid spacings to yield accurate results. Consequently, use of 4 He for recording diffusion kinetics is best for internal shards of large, minimally zoned samples (e. g. , the Durango apatite standard). However, apatite and zircon crystals with these characteristics are rare, proton-irradiation to generate 3 He is expensive, and many (U-Th)/He labs lack the magnetic sector noble gas mass spectrometer instrumentation needed   4  for complete details. for 3 He analyses, so for practical reasons many diffusion experiments are conducted with 4 He on typical minerals while keeping data interpretation caveats in mind.
Kinetic Data and Reporting (Checklist in Table 4) Table  4  is a reporting checklist that includes "minimum needed" and "recommended" reporting for kinetic data, uncertainties, and associated information. The core measured data that should be documented for kinetic experiments are simple: temperature and duration of each step or interval and the amount of gas released for each temperature step or interval. The minimum needed derived data are: values of 10,000/K and ln(D/a 2 ) for Arrhenius plots, the diffusion geometry assumed and equations used for calculation of ln(D/a 2 ) values, values of D 0 /a 2 and E a determined by linear regression through the data, as well as the criteria used in selecting data for regression and the nature of the regression algorithm. To make data more immediately useful it is also recommended to report the cumulative fraction of gas lost, f, which represents simple derived data that are essential input to diffusion calculations.
Additional temperature uncertainty is introduced by measurement of sample temperature by a thermocouple or pyrometer that may not be exactly co-located where the grain sits in its metal packet or envelope. While measurement precisions of ± 1 °C are possible, realistic uncertainties in temperature accuracy are probably closer to 5 °C or even 10 °C. Whether inaccuracy during stepped-heating is systematic or random is debatable; both are possible. Propagation of the analytical uncertainties for the calculation of diffusivity and then Arrhenius parameters from stepped-heating data is not difficult but rather involved numerically. The fractional loss values that are the key inputs are ratios of accumulated measured amounts of the diffusant under study; counter-intuitively, while small early steps may seem imprecise, their estimate of fractional loss is usually quite good.
Additionally, in Arrhenius space, there is strong error compression of diffusivity values due to the logarithmic term. See  Ginster and Reiners (2018)  for additional discussion of uncertainty propagation for diffusivities and diffusion parameters. Note that the accuracy of the derived kinetic parameters is subject to the choice of data used for the linear regression to determine D 0 /a 2 and E a and to the assumptions outlined in sections 8. 2. 1 and 8. 2. 2. Thus, it is important to explain the criteria for choosing the data to regress and to discuss the relevant considerations.
4 He/ 3 He Data, Uncertainties, and Reporting (Checklist in Table 4) Table  4  notes the information needed for 4 He/ 3 He reporting. Because date determination is typically part of 4 He/ 3 He analysis, all of the sample-related data required for a conventional (U-Th)/He analysis should be reported (e. g. , sample information, parent and daughter absolute amounts; grain dimensions, F T ; see Tables  1 2 3 ). The facility for and conditions of irradiation should be described. Essential data measured to report include the temperature and duration of each step (to permit assessment of gas release and kinetics) as well as the amounts of gas released at each heating step. The latter can be done in one of two ways: the 3 He amount released at each step and the 4 He/ 3 He ratios of those steps or the amounts of 4 He and 3 He released at each step.
After heating is complete, the system has cooled, and any residual active gases have been fully gettered, a reference standard is added to determine the total 4 He released, as in conventional analysis. During analysis, it is important to monitor active gas species such as H and m/e = 28 to ensure that gettering is sufficient to prevent their levels from becoming too high; in large amounts, these gases can lead to significant changes in instrument sensitivity  (Guo et al. , 2021). To date, the CRH method has only been applied to 4 He release from apatite. Because the data take the form of a cumulative fractional loss curve (Fig. 10C , top plot) and because the ramped thermal history is known, CRH data can be treated as normal steppedheating data for the purposes of calculating diffusivities, subject to the considerations for 4 He diffusion data noted in section 8.
Uncertainties on at least the temperatures and He beam values or amounts need to be reported, and given the continuous nature of CRH experiments and the range in signal sizes and temperatures encountered, the protocol of estimating uncertainties at any one point should be described. Finally, how the final 4 He signal measured by the mass spectrometer at the end of experiment was converted to an absolute amount with an uncertainty should be documented. As for kinetic and 4 He/ 3 He work, tabulating the cumulative fractional loss is recommended. If CRH data are used to derive ki-netic information, then the additional relevant information should be reported (sections 8. 2. 3 and 8. 2. 4; Table  4 ).
Baseline Demographic and Biological Data Age, sex, body mass index, and metabolic risk factors were recorded at inclusion. Accurate data regarding the consumption of alcohol, tobacco, cannabis, and coffee were recorded using a self-questionnaire. To verify the inclusion criteria, blood samples were taken on the day of hospitalization or the day after. On the same day as TE and liver biopsy, we measured AST, alanine aminotransferase (ALT), gGT, platelets, hyaluronic acid, and a 2macroglobulin levels. Bilirubin was not measured routinely during alcohol detoxification, and we measured bilirubin retrospectively in frozen (-80 C) sera taken the day of the biopsy, when available.