dataesr/scientific-paragraphs-categorization huggingface dataset:
Both were objectives of the TreeTrace project. The difficulty in such studies performed in an industrial context is that very few information is available on the site and logs sampled since the trees and logs were already cut when we arrived for sampling. We give below some examples of past uses of the database: An automatic reading algorithm of the black and white calibration scale was designed by  Delconte (2019). Decelle and Jalilian (2020) proposed a neural network algorithm for automatic segmentation of the wood cross-section in the raw images taken in the forest or after transportation to Freiburg. The superiority of convolutional neural networks for the identification of log cross-sections over methods adapted from fingerprint or iris recognition techniques was demonstrated in the comparative study by  Wimmer et al.
Plus, brachiopod shell Mg content has been found to have a strong taxonomic trend, with shells of thecideid and craniid brachiopods being made of high-Mg calcite in contrast to the low-Mg calcite of rhynchonellide and terebratulide brachiopod shells  (Brand et al. , 2003; Ullmann et al. , 2017). This undermines the brachiopod shell MgCO 3 -temperature relationships which uses a dataset that consists of thecideid, rhynchonellide and terebratulide  (Brand et al. , 2013 (Brand et al. , , 2019)). While Sr/Ca ratios are mostly used to assess the shell preservation of fossil specimens  (Brand and Veizer, 1980) , this ratio also constitutes a potential marine paleothermometer applicable to brachiopod shells, as is the case for corals  (McCulloch et al. , 1994; Shen et al. , 1996; Marshall and Mc-Culloch, 2002; Swart et al.
9 and 25. 5 • C. We discuss the validity and robustness of our oxygen isotope fractionation equation established with measured δ 18 O c of calcite and with seawater temperature and δ 18 O w estimated from oceanographic data. The dependence of elemental ratios on seawater temperature is discussed in light of this new available dataset of modern brachiopods. Finally, we highlight kinetic effects as non-negligible sources of isotopic and trace element variability.
Carbon and oxygen stable isotopes The whole dataset of δ 13 C and δ 18 O values (n = 73) from modern-brachiopod shells ranges from -2. 2 ‰ to 3. 2 ‰ and from -1. 2 ‰ to 4. 0 ‰, respectively. There is a robust negative linear correlation (R 2 > 0. 73, p slope < 0. 001) between 18 O c-w (= δ 18 O c -δ 18 O w ) and MAT (Fig. 1 ; Table  3 ). The correlation observed in bulk shell samples is indistinguishable from that in inner-layer samples (Fig. 1a ). On the contrary, the correlation obtained from outer-layer samples shows a significant offset in relation to both innerlayer and bulk-layer samples. This is in line with the differences between the outer and inner layers observed within the same specimen, which are in most cases above analytical uncertainties and range from -3. 7 ‰ to -0. 2 ‰ (mean = -1.
66 < R 2 < 0. 93 for the whole dataset), especially when considering only inner-layers sample (0. 84 < R 2 < 0. 96). No significant correlation (p slope > 0. 2) of Mg/Ca with temperature is observed in the dataset (Fig. 1 ; Table  3 ). Measured element / Ca ratios are systematically higher in the outer layers than in the inner layers of brachiopod shells (Student's t test: p < 0. 01; Fig. 1c-e ).
6 ‰ at tropical temperatures (20-30 • C; Fig. 2a ), with the equation from  Brand et al. (2019)  predicting a lower fractionation factor. At temperate and polar temperatures (20 to 0 • C), our new equation highlights a higher sensitivity of oxygen fractionation to temperature than that of  Brand et al. (2019; Fig. 2 ). The two equations overlap at around 10 • C and deviate substantially around ∼ 0 • C, with a 18 O c-w difference of up to ∼ 1 ‰ between the equation of  Brand et al. (2019)  and our equation (Fig. 2a ), a pattern also observed in the geochemical datasets (Fig. 2b ). Examining the geochemical dataset revealed that the large offset between the two equations at low temperatures partly results from the use of a second-order regression model by  Brand et al. (2019) , as the regression curve overlaps with the highest 18 O c-w data points at temperatures of ∼ 1 • C.
We preferred to use a linear regression that was more appropriate to data in the low-temperature (< 50 • C) linear domain of the hyperbolic curve (α = f (1/T 2 )) predicted by equilibrium thermodynamics. Still, the main discrepancies between the equation proposed herein and that of  Brand et al. (2019)  are mainly driven by a difference in the geochemical dataset. The case of the polar brachiopods Liothyrella uva from the island of Rothera (Antarctica) highlights the likely reasons for this discrepancy at low temperatures. Indeed, δ 18 O values reported in both studies are the same  (Brand et al. , 2019) , indicating that the discrepancy lies in the environmental parameters used to derive the equation. Brand et al. (2019)  used published environmental parameters measured locally in late February for this site, while we approached this estimation using regional annual averages.
This difference in integration time of the environmental parameters is important be-   (Meredith et al. , 2013). This particular brachiopod species has a higher growth rate during the Austral winter than during the Austral summer  (Peck et al. , 1997) , further increasing the likely seasonal bias. These discrepancies are individually relatively small (± 1-2 • C; ±0. 5 ‰ VSMOW), but put together, they easily explain the 1 ‰ offset between both equations in the low-temperature range. We use a published independent dataset of modernbrachiopod δ 18 O values  (Bajnai et al. , 2018)  to test our equation against other published equations in their ability to predict environmental temperatures when δ 18 O sw is known (Fig. 3 ). This dataset has a MAT range of 0 to 29 • C and uses two sets of δ 18 O sw for most data, one derived from direct measurements and one derived from δ 18 O sw -salinity relationships  (LeGrande and Schmidt, 2006).
Plus, Mg/Ca values are available for all samples, allowing us to apply the equation of  Brand et al. (2013)  to the dataset. Isotopic temperatures were calculated and then normalized as the temperature deviation from environmental temperature ( T in • C) with full propagation of uncertainties. Of all the equations tested, the equations derived from measurements of modern brachiopods  (Brand et al. , 2013 (Brand et al. , , 2019;;  this study) yield the most accurate temperature predictions. Mean T are statistically indistinguishable from 0, using salinity-based δ 18 O sw estimate results for all four equations. Interestingly, the accuracy of isotopic temperature estimates is poorer when measured δ 18 O sw values are used. The equations of  Brand et al. (2013 Brand et al. ( , 2019) )  now significantly underestimate growing temperatures (Fig.
3 ; p (mean T = 0) < 0. 01), while our equation yields mean T values that are statistically indistinguishable from 0 (p (mean T = 0) = 0. 11). The equation of  Kim and O'Neil (1997) , derived from synthetic carbonates, and that of  Epstein et al. (1953) , derived from molluscs, both underestimate the growing temperature of brachiopod shells (Fig. 3 ; p (mean T = 0) < 0. 001) in both δ 18 O sw hypotheses. On the other end of the spectrum, the equation of  Daëron et al. (2019) , derived from slow-growing calcite, overestimates the growing temperature of brachiopod shells (Fig. 3 , p (mean T = 0) < 0. 001) in both δ 18 O sw hypotheses. Although it lessens the accuracy of δ 18 O temperatures in this dataset, the use of locally measured δ 18 O sw values over the salinity-based estimates improved their precision (4.
0 < 2σ < 5. 3 • C, n = 13 rather than 5. 4 < 2σ < 6. 4 • C, n = 18). Independent from the fractionation equation or the δ 18 O sw value used, temperature estimates are associated with large scatter of more than 4 • C (2σ ) around mean T. We suggest that this scatter is related primarily to the variability of brachiopod shell δ 18 O values observed within a population (Fig. 2 ;  Brand et al. , 2019)  due to isotopic fractionation mechanisms other than temperature-dependent fractionation, namely kinetic effects, metabolic effects and pH effects. Using the MgCO 3 -corrected equation of  Brand et al. (2013)  instead of that of  Brand et al. (2019) , both derived from very similar datasets, has the only effect of slightly improving the precision of the estimates, decreasing the scatter by ∼ 0. 6 • C around the mean deviation from environmental temperatures.
This effect is about 1 order of magnitude below the remaining dispersal of data. 3. For the different equations derived from modernbrachiopod data, we push further the comparison of the deviation between isotopic temperature calculated with the different equations and environmental temperatures and look at the distribution of these offsets ( T ) against seawater temperature (Fig. 4 ). This highlights a significant correlation between T and seawater temperature when applying both the equations of  Brand et al. (2013 Brand et al. ( , 2019) )  to the comparative dataset of  Bajnai et al. (2018;  p uncorrelated < 0. 001; Fig. 4 ). On contrary, there is no significant correlation between T and seawater temperature when applying both our new equations to the comparative dataset of  Bajnai et al.
(2018;  p uncorrelated > 0. 3). This comparison highlights that the application of the equations of  Brand et al. (2013 Brand et al. ( , 2019) )  does not completely account for temperature as an explicative variable for brachiopod 18 O c-w in the dataset of  Bajnai et al. (2018). In the following, we further assess the impact of trace element incorporation in brachiopod calcite on the fractionation factor between calcite and water using our new data. Bra-chiopod calcite can be viewed as a three-component molar mixture of CaCO 3 , MgCO 3 and SrCO 3 , and the fractionation factor of this mixture ( brach. calcite-water ) of divalent metal carbonates is equivalent to the sum of the mineral-water fractionation factors weighted from the mineral molar fractions. This bulk isotopic fractionation factor is thus expressed as follows: (brach.
Brachiopod shell clumped isotopes: an alternative paleothermometer? Although there is a strong correlation between our new 47 values from brachiopod shells and growing temperatures, 47 values at a given temperature are generally higher than what is expected from the state-of-the-art equation of  Anderson et al. (2021; Fig. 5 ). This observation is in line with the results of  Bajnai et al. (2018)  gathered in the CDES reference frame. To discuss modern-brachiopod 47 values in relation to a larger dataset, the data from  Bajnai et al. (2018)  were adjusted to the CDES 90 reference frame for better comparison with our dataset in the I-CDES reference frame  (Bernasconi et al. , 2021). We acknowledge that the different standardization protocols used for the two datasets could hamper the   Bajnai et al.
, 2020; Fiebig et al. , 2021). The 47 -temperature relationship derived from this combined brachiopod dataset yields the following equation: 47(I-CDES90 • C) = 0. 042±0. 002× 10 6 T 2 +0. 124±0. 016, (5) with 47 (I-CDES90 • C) in ‰ and T being the temperature in K. This equation, while still nearly within the error of the equation of  Anderson et al. (2021; Fig. 5b ), highlights systematically higher brachiopod 47 values relative to what is expected from the canonical clumped isotope equation. A similar underestimation of 47 temperatures using the equation of  Anderson et al. (2021)  was recently reported on culture-grown bivalves  (de Winter et al. , 2022). The authors argued that the 47 -1-T 2 relationship is non-linear, implying that equations including warm (> 100 • C) data points, such as that of  Anderson et al.
, 2018; Peral et al. , 2018 Peral et al. , , 2022;; Daëron et al. , 2016; Meinicke et al. , 2020 Meinicke et al. , , 2021)) , laboratory-precipitated calcites  (Jautzy et al. , 2020; Anderson et al. , 2021; Fiebig et al. , 2021) , slow-growing cave calcites  (Daëron et al. , 2019; Anderson et al. , 2021; Fiebig et al. , 2021)  and bivalve calcite  (Huyghe et al. , 2022). This observation is more relevant in the  Bajnai et al. (2018)  dataset, with a mean 47 temperature deviation from seawater temperatures of -5. 6 ± 1. 6 • C (2 SE, n = 18), than in our new dataset, with a mean 47 temperature deviation from seawater temperatures of -2. 4 ± 1. 3 • C (2 SE, n = 19; Fig. 5a ). However, we argue that the difference between the two datasets of modern-brachiopod 47 may largely result from distinct taxonomic assemblages and/or sampled locations in both datasets.
Indeed, our new 47 data from New Zealand brachiopods agree very well with previous data from the same brachiopod species and similar locations  (Bajnai et al. , 2018 ; see File S3 in the Supplement). The  Bajnai et al. (2018)  dataset is dominated by brachiopods from the suborder Terebratellidina (12/18), a group for which the combined dataset shows the most deviation from the  Anderson et al. (2021)  equation at low (-2 to 5 • C) temperatures but most importantly in the middle (8-15 • C) temperature range (Fig. 5c ). This group is associated with a mean 47 temperature deviation from seawater temperatures of -5. 6 ± 1. 7 • C (2 SE, n = 19) when applying the  Anderson et al. (2021)  equation, while the other most represented group in the com-bined dataset, the suborder Terebratulidina, better fits the canonical equation (Fig.
Mg/Ca thermometer for brachiopod shells Our Mg/Ca data obtained from the inner layers of brachiopod shells do not show any significant correlation with growth temperature (p = 0. 94; Fig. 1c ; Table  3 ), at odds with the strong correlation between the Mg/Ca molar ratio of the brachiopod shell secondary layer and the growth temperature found by  Brand et al. (2013 Brand et al. ( , 2019)). However, these au-thors acknowledged that some species do not follow the trend they illustrated as the GBMgL and suggested that such deviations resulted from either lower growth rates  (Brand et al. , 2013)  or higher growth rates  (Brand et al. , 2019)  of the considered species relative to other brachiopods. This issue alone illustrates how, from the largest dataset of modern brachiopods available so far (i.
e. Brand's database), one cannot firmly determine whether or not Mg/Ca correlates with seawater temperatures. We emphasize that our dataset lacks brachiopod shell samples from equatorial surface marine waters (27 • C < T < 32 • C), which record the highest MgCO 3 molar content in Brand's database  (Brand et al. , 2013 (Brand et al. , , 2019)). Interestingly, the highest MgCO 3 contents reported by these authors were measured on brachiopods belonging to the order Thecideida. This taxonomic singularity is of prime importance because (1) Thecideide brachiopod shells are essentially made of a shell fabric unique to its group  (Simonet Roda et al. , 2022) , and secondary shell fabric (fibrous layers, which form the majority of Rhynchonellida and Terebratulida shells) is restricted to small areas of the shell, such as the teeth and the inner sockets  (Williams, 1968 (Williams, , 1973;; Baker, 2006) ; (2) Thecideide shell is formed from high-Mg calcite  (Ullmann et al.
, 2017). The exclusion of Thecideida data from the database published by  Brand et al. (2013)  produces a substantially weaker (R 2 = 0. 23) yet significant (p < 0. 01) correlation between shell Mg/Ca and temperature. In addition, magnesium has also been shown to be more concentrated in major growth bands  (Gaspard et al. , 2018; Müller et al. , 2022)  than in other parts of the secondary shell layer in articulated brachiopods, which could explain the high Mg/Ca values observed from slow-growth and long-lifespan brachiopods  (Brand et al. , 2019) , especially when considering samples obtained from a large sampling area covering multiple growth lines. Given our new data and all these considerations, the brachiopod Mg/Ca should be regarded as an unreliable proxy for annual or seasonal temperature reconstructions, at least in the -2 to 25 • C range (Fig.
Potential of other trace element / Ca proxy Our new brachiopod Sr/Ca data show a significant but weak negative correlation with ambient temperature (p slope < 0. 001; R 2 < 0. 40). This correlation is supported by a weak positive correlation between Sr/Ca and 18 O c-w of the inner layers (p slope < 0. 01; R 2 = 0. 31), as we also expect 18 O to decrease with increasing temperatures (i. e. Sect. 4. 1). This contradicts the pioneering findings of  Lowenstam (1961) , which suggested a negative correlation between brachiopod shell Sr/Ca and 18 O c-w. The brachiopod database of  Brand et al. (2013)  shows no significant correlation between Sr/Ca and temperatures (p slope = 0. 20). Given the diverging conclusions from one dataset to another, Sr/Ca values of brachiopod shells do not appear to be controlled by growing temperatures at the first order.
7). A wider look at the geochemical dataset highlights very strong correlations of Sr/Ca, Li/Ca, and Na/Ca ratios in brachiopod shells with one another (0. 68 < R 2 < 0. 92; p slope < 0. 01) over the whole dataset and particularly from inner-layer samples (0. 87 < R 2 < 0. 97; p slope < 0. 01). Correlation in our dataset is strongest between Sr/Ca and Na/Ca and weakest between Sr/Ca and Li/Ca. Similar correlation trends also appear at the intra-specimen level  (Romanin et al. , 2018; Rollion-Bard et al. , 2019). Such strong correlations, at both intra-individual and inter-specific scales, may suggest that the first-order variability of those different element concentrations within brachiopod shells may be explained by similar processes, either environmental or biological. Ullmann et al. (2017)  reported a distinct geochemical signature between brachiopods species, especially within the Mg/Ca-Sr/Ca space.
Our inner-shelllayer dataset presents a similar distribution within the low-Mg/Ca range (< 10 mmol / mol), where Sr/Ca ratios of Terebratulidina shells are distinctly lower than those of Terebratellidina shells. Owing to the strong correlation between Sr/Ca, Li/Ca and Na/Ca, our dataset differentiates between Terebratulidina shells with low element / Ca ratios (0. 4 < Sr/Ca < 0. 7 mmol / mol; 0 < Li/Ca < 10 µmol / mol; 1 < Na/Ca < 4 mmol / mol) and Terebratellidina shells with high element / Ca ratios (0. 9 < Sr/Ca < 1. 2 mmol / mol; 35 < Li/Ca < 60 µmol / mol; 8 < Na/Ca < 12 mmol / mol), with the exception of the Antarctic brachiopod Liothyrella uva (Broderip, 1833; Terebratulidina) which shows the highest Sr/Ca, Na/Ca and Li/Ca values (Fig. 6a-b ). With this exception and that reported by  Ullmann et al.
(2017) , a taxonomic relationship is not satisfactory, especially considering the significant yet noisy relationship between element / Ca and environmental parameters such as temperature and salinity within our new dataset. Indeed, we also observe a strong relationship between brachiopod shell element / Ca values and geographical location (Fig. 6c-d ). Tropical shells (Guadeloupe and New Caledonia -only Terebratulidina) have low element / Ca values, the middle latitudes (New Zealand and Crozet Islands -dominated by Terebratellidina) have intermediate to high element / Ca values, and polar brachiopods (Antarctica and Norway -mixed assemblage) have high element / Ca values. Despite this firstorder distribution, it appears that, within the same environment, species difference appears to dominate, as is the case in Doubtful Sound (New Zealand), where Terebratella sanguinea (Leach, 1814; Terebratellidina) shells have higher element / Ca values than Liothyrella neozelanica  (Thomson, 1918; Terebratulidina)  shells.
Our new data suggest that temperature is not the prime parameter that can describe trace element incorporation into articulated brachiopod shell calcite from a dataset of widely distributed and taxonomically diverse brachiopods. This conclusion does not exclude the possibility of any temperature control on trace element incorporation in brachiopod shell calcite, which may be relevant at the species level, as proposed by  Butler et al. (2015)  and observed in other calcifying organisms such as bivalves  (Freitas et al. , 2006)  and foraminifera  (Anand et al. , 2003). However, the influence of other controls on trace element incorporation in brachiopod shell calcite (growth rate, environment fluid chemistry, etc. ;  Jurikova et al. , 2020)  is strong enough to blur the likely temperature control so that the trace element / Ca ratios studied here are not suited to being used as paleothermometers.
Precipitation of brachiopod shell calcite out of equilibrium with seawater Our new data confirm that brachiopod shell calcite does not precipitate in isotopic equilibrium with seawater, as highlighted by the significant deviation from thermodynamic isotopic equilibrium relationships constrained from very-slow-growing calcite  (Daëron et al. , 2019; Anderson et al. , 2021, Figs. 2-5). It is worth noting that most brachiopod shell δ 18 O data  (Brand et al. , 2019; this study)  plot in between thermodynamic equilibrium isotopic fractionation  (Daëron et al. , 2019)  and the equation of  Kim and O'Neil (1997; Fig. 2). The deviation of brachiopod shell calcite δ 18 O from thermodynamic equilibrium ( 18 O eq = δ 18 O brach. calcite -δ 18 O equilibrium ) is obvious when we compare our dataset to the equation of  Daëron et al.
(2019)  in the clumped isotope-oxygen isotope fractionation space (Fig. 7a ), with most of our dataset showing higher 47 and lower δ 18 O than predicted (Fig. 7b ), a feature previously highlighted by  Bajnai et al. (2018). As a result, brachiopod calcite shows apparent 47 and δ 18 O temperatures that are, respectively, lower and higher than those predicted by the thermodynamic equilibrium. This deviation from equilibrium values has a 47 -18 O eq slope of 0. 019 ± 0. 005 in our new brachiopod dataset, indistinguishable from the slope of 0. 017 ± 0. 003 reported by  Bajnai et al. (2018)  using δ 18 O sw values from the δ 18 O sw database  (LeGrande and Schmidt, 2006). Brachiopod shell 18 O data  (Brand et al. , 2003 (Brand et al. , , 2013 (Brand et al. , , 2019;;  this study) also show a large geochemical variability among brachiopods sampled from similar marine environments (T , S), with a 18 O range often higher than 1 ‰ (Fig.
3 ;  Brand et al. , 2019). Isotopic fractionation equations  (Brand et al. , 2013 (Brand et al. , , 2019;;  this study) usually rely on 18 O c-w values plotted against mean annual temperatures. Thus, it would be tempting to attribute such scattering of data to seasonal variations in both temperature and δ 18 O sw , but this would only apply to specimens that lived above or in the upper part of the thermocline. Such isotopic scattering is indeed expected if we consider datasets based on multiple sampling along the growth axis of an individual  (Yamamoto et al. , 2011; Takayanagi et al. , 2015) , such as in the case of  Brand et al. (2013 Brand et al. ( , 2019)). However, seasonal scattering in data resulting from intra-individual geochemical variability is unlikely for our measurements, which are performed on a large sampling area that should correspond to multiple months or years of growth.
Non-equilibrium fractionation and kinetic effects in brachiopod shell calcite as evidenced by clumped isotopes and oxygen isotopes. (a) Plot of brachiopod inner shell layers in the 47 -1000 ln α (calcite-water) space compared with the equilibrium line (blue line) defined by very-slow-growing abiogenic calcite  (Daëron et al. , 2019; Anderson et al. , 2021). The red highlight shows the results from A. kerguelenensis (Crozet Islands) and their expected geochemical values on the equilibrium line. Note the negative correlation between 47 and 1000 ln α (calcite-water) evidenced in this subset. (b) δ 18 O c and 47 offset from their expected equilibrium values calculated from environmental parameters using the equations of  Daëron et al. (2019)  and  Anderson et al. (2021) , respectively. The trends followed by these offsets within our new dataset are similar to those reported from other brachiopod samples by  Bajnai et al.