dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion Our comparison of the 2004 and 2022 databases reveals that no harlequin toad went from status shrinking to steady. We reject the hypothesis that we have entered a hypothetical post-decline phase of improvement. Although reports on sudden and rapid population declines have lessened (Supplementary Table  2 ), many species continue to have shrinking populations, which implies that over time declines continue to happen more silently. This is reinforced by the observations that of the 29 species rediscovered since 2004, six have not been seen again for the past 10 years, despite targeted searches  10. These harlequin toads either occur in low numbers or are possibly extinct emphasizing that rediscoveries are not equating recoveries. At the same time habitat destruction and Bd persist to threaten harlequin toads, despite that 96 (75%) of the species occur in protected areas and (at least) some Atelopus can somehow cope with Bd.
Methods We used the original database of La Marca et al. 9  , which compiled information from experts on Atelopus population trends through February 2004. This database was updated with the revised taxonomy, as well as additional input and data from experts, and our study period was defined as March 2004 to December 2022 (Supplementary Table  1 ). We interviewed 105 experts (a diverse group of scientists and conservationists with considerable knowledge on Atelopus species), sometimes on multiple occasions, from October 2019 to December 2022. All 75 original database contributors to La Marca et al. 9  were contacted, but we received updated information from only 13. The additional 92 contributing researchers were Atelopus taxonomists and conservationists. Original contributions included initial estimates on population status and general threats as well as field data on the species ecology and threats at the site level.
Data was reviewed and summarized species-wise prior to a second round, where experts were able to provide corrected estimates, as has been proven successful for obtaining robust expert data  48, 49. Still, we are well-aware that expert opinions carry an unavoidable uncertainty and need to be considered carefully  49, 50. Most of the experts who contributed data also contributed to the writing of this paper and became co-authors. In this study, we refer the term 'species' to described taxa that we consider valid and to forms that are undescribed and are expected to represent valid species. Also, we tentatively consider suggested subspecies as species here. According to this, we refer to 131 species of which 100 are formally described, while the 2004 database considered 94 taxa. Alphataxonomic problems remain for some harlequin toads, e.
g. A. hoogmoedi which could be more than one species  51. Following La Marca et al  [. 9  , for each species we updated the information on distribution, the known altitudinal range, and local endemism by number of known populations (1, 2, >2). We recorded: species population status; the year last seen (YLS); information on Bd presence; occurrence in any governmental or private protected area. In order to address threats that have been identified to play a key role in Atelopus declines  9, 34  , we additionally assessed the potential future impact of climate change for each species. For detailed data see Supplementary Table  1. Details on how data were assessed are described below. The population status was coded following definitions of La Marca et al. 9. However, we change the terminology to avoid confusion with terms used by the IUCN Red List of Threatened Species.
Freeman-Halton extension of Fisher's exact tests (one-sided, with sequential Bonferroni-Holm correction) were performed to explore the population status change between the 2004 and 2022 databases using the following online web statistical calculator: https://astatsa. com/FisherTest/ (accessed 7 January 2023). In addition to information on Bd presence through direct testing of Atelopus specimens (including diagnosis both by PCR or histology), we provide information on presumed Bd presence for Atelopus species that have not been tested for Bd. We consider likely presence of Bd in an Atelopus species when Bd infection is known in other amphibian species at Atelopus localities. For this purpose, we used Bd records available from the Aquatic Parasite Observatory (http://www. aquaticparasites. org/, accessed 8 June 2022) and the Amphibian Disease Portal (https:// amphibiandisease.
CSI data were downloaded from Figshare (https://doi. org/10. 6084/m9. figshare. 14672637, accessed 2 March 2022). CSI values range 0-1 (most to least stable). With the goal of obtaining information on Atelopus conservation breeding, we contacted all existing institutions, to our knowledge, that hold or held captive assurance colonies of harlequin toads to compile a dataset on the species kept and breeding success (Supplementary Table  4 ). We received information from all seven institutions located in Atelopus range countries as well as from numerous North American and European institutions, partially coordinated through the multinational Project Golden Frog  38. Reporting summary. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Acknowledgements For help with gathering data on harlequin toads we are grateful to the following colleagues  Marvin Anganoy-Criollo ,  Ariadne Angulo ,  Jimy Barrantes-Madrigal ,  Leonardo Batallas ,  Merilyn A. Caballero Arias ,  Euclides Campos ,  Mauricio Carpio ,  Daniel Chávez ,  Patricio Dominguez ,  Rogemif D. Fuentes M. ,  Gustavo Gonzalez Duran ,  Gustavo Gutiérrez ,  Paul Houser ,  Astrid Lizondro ,  Felipe Lievano ,  Albertina P. Lima ,  Madian Miranda ,  Daniel Orizano ,  Luis Oyagata ,  Daniel Padilla Jiménez ,  Luis Pino ,  Sergio Quiroz ,  Héctor E. Ramírez-Chaves ,  Ángel Sosa-Bartuano ,  Samuel Valdes , and  Andrés Viuche Lozano. Christopher Heine  kindly provided a photograph used in Fig. 1. We also thank the entire  Atelopus Survival Initiative  for support and  Luis F.
2011) , which shows chromospheric and coronal emission consistent with a correspondingly high level of stellar activity  (Czesla et al. 2013; Staab et al. 2017). Due to its short orbital period of only 0. 81 d and the small orbital distance of 0. 015 AU (see Table  1 ), WASP-43b is thought to be tidally locked, making it a suitable target to analyse variabilities across its atmosphere based on phase curve observations. Previous observational data include a low-resolution transmission spectrum and emission phase curves from the Hubble Wide Field Camera 3  (Bean 2013) , as well as two datasets in the infrared region measured with the Spitzer InfraRed Array Camera  (Blecic et al. 2014). Kreidberg et al. (2014)  first found evidence for H 2 O absorption and emission, while  Chubb et al. (2020)  recently reanalysed the data and reported evidence for the presence of AlO being favoured over all other investigated molecules.
Based on this result, they conclude that the C/O ratio is consistent with the solar value. Benneke (2015)  found an upper limit of C/O < 0. 87 in a reanalysis of the data, while  Irwin et al. (2020)  included the Spitzer/IRAC observations to retrieve C/O ∼ 0. 91. However, they caution that the abundances of CO and CH 4 effectively only depend on the two Spitzer datasets. The data reduction and assumed thermal profile thus have a strong influence on the retrieved C/O ratio, such that  Changeat et al. (2021)  recovered C/O = 0. 68 with slightly different methods and assumptions. Using the large simultaneous wavelength coverage and high resolution (R ∼ 100 000) of ground-based spectrographs such as CRIRES + mounted on the ESO VLT/UT3 telescope, it becomes possible to circumvent dependencies on a limited number of measurements and the ensuing ambiguities.
Observation and data reduction We observed WASP-43b on 11 March 2022 and 20 February 2023 with the CRIRES + instrument as part of the guaranteed time observations of the CRIRES + consortium. The two observing runs were conducted shortly before and shortly after the secondary eclipse, respectively, to observe the dayside of WASP-43b (see Fig. 1  for the phase coverage). We used the nodding mode technique to observe the target alternating between two different positions (A and B) along the slit to allow for the removal of detector artefacts and the sky background during the extraction. In our further analysis, we combined the A and B spectra to form a single time series for each night. We observed in the K2192 wavelength setting covering parts of the wavelength region from 1972 nm to 2486 nm with an exposure time of 300 s.
Generating planetary model spectra The synthetic model spectra for the cross-correlation analysis were computed with the radiative transfer code petitRAD-TRANS  (Mollière et al. 2019 ), using the CO, H 2 O and CO 2 line lists of  Rothman et al. (2010) , the CH 4 line list of  Hargreaves et al. (2020) , the HCN line list of  Harris et al. (2006)  and  Barber et al. (2014) , and the NH 3 line list of  Yurchenko et al. (2011). We assumed a non-inverted temperature-pressure  (T -p) profile characterised by the parametric model from  Guillot (2010). This model is determined by the irradiation temperature T irr , the internal temperature T int , the infrared opacity κ IR and the ratio of visible to infrared opacity γ (see his Eq. (  29 )). Based on the assumed volume mixing ratios (VMRs), we calculated the mean molecular weight and subsequently the mass fractions of these molecules, assuming a solar-like VMR ratio between H 2 and He.
Retrieval framework The properties of the atmosphere of WASP-43b were analysed by performing an atmospheric retrieval, in which the observed data is compared to a large number of different models. Using a sampling algorithm to determine the posterior distributions of  the model parameters allows for the statistical measurement of atmospheric characteristics. In this way, any properties that have an effect on the observed emission spectra can be analysed. Both the T -p profile and the abundances influence the line strengths, while the position of the lines over the course of the observing run depends on the K p and systemic velocity. Additionally, the equatorial velocity v eq can be determined as a rotation increases the line width by means of rotational broadening. The existence of clouds at a certain pressure P cloud truncates the spectral lines across the entire wavelength range as contributions from regions below the cloud deck are blocked.
Accounting for smearing of the signal Due to its short orbital period, the radial velocity of WASP-43b changes significantly during a single exposure of 300 s. For night 1, the velocity difference between start and end of an exposure was between 2 and 5 km s -1 , causing a substantial smearing of the spectral lines. To account for this effect, the model was interpolated to the same wavelength grid as the 2D data (wavelength × time), resulting in a model matrix M. The model could then be shifted according to the planetary Doppler velocity (see Eq. (  2 )). For each exposure, we calculated these radial velocities at the beginning and end time, shifted the model to ten evenly spaced planetary rest-frames between these two velocities, and computed the smeared model as the mean over the ten sub-exposures.
Likelihood function To retrieve the atmospheric properties, we applied a Markov chain Monte Carlo (MCMC) algorithm using the EMCEE package  (Foreman-Mackey et al. 2013)  to the logarithm of the likelihood function  (Hogg et al. 2010; Yan et al. 2020) : ln(L) = - 1 2 i, j (R i, j -M i, j ) 2 (βσ i, j ) 2 + ln(2π(βσ i, j ) 2 ) , (4) where R i, j is the residual spectrum at pixel index i and time j, M i, j is the 2D matrix of a filtered model spectrum, σ i, j are the uncertainties of the residuals and β is a scaling factor to σ i, j. For the MCMC, we used 32 walkers with 15 000 steps each. We chose uniform priors for all input parameters, which are summarised in Table  4.
3. 3. Figures  7  and B  We detected the presence of CO and evidence for H 2 O in the first night. However, we were not able to find either of the species in night 2. This does not come as a surprise, because the data quality of night 2 is considerably worse (see Sect. 2). We assessed the quality of night 2 by injecting a signal with the expected strength, and were not able to recover it. Therefore the non-detection in night 2 is most likely due to the poor data quality. Pino et al. (2022)  showed that principal component analysis algorithms remove much of the planetary signal at phases close to quadrature, as there is only a small shift in the line positions. This could affect especially the signal in night 2, as the A23, page 7 of 15 observation started at a phase of 0. 28. Using an injectionrecovery test, we determined that SYSREM removes a substantial amount of the planet signal at phases up to 0.
The retrieved super-solar metallicity matches with findings of  Kreidberg et al. (2014, [M/H]  = 0. 4-3. 5 × solar) and  Stevenson et al. (2017, 0. 4 -1. 7 × solar) , while it is lower than the estimates of  Kataria et al. (2015, 5 × solar)   Many previous studies used the Spitzer datasets to constrain the C/O ratio, and these results show a strong dependency on the reduction method and assumed thermal profiles  (Changeat et al. 2021). The observations presented in this work cover the CO band head in the K band with the high resolution of CRIRES +. Therefore the determination of the CO abundance does not rely on individual data points, as it is informed by a large number of CO absorption lines. Nevertheless, similar to previous works the retrieved C/O ratio is only based on two molecular species, as we were not able to detect other carbon-and oxygen-bearing molecules.
Acknowledgements. CRIRES + is an ESO upgrade project carried out by  Thüringer Landessternwarte Tautenburg ,  Georg-August Universität Göttingen , and  Uppsala University. The project is funded by the  Federal Ministry of Education and Research (Germany)  through Grants  05A11MG3 ,  05A14MG4 ,  05A17MG2  and the  Knut and Alice Wallenberg Foundation. Based on observations collected at the  European Organisation for Astronomical Research  in the Southern Hemisphere under ESO programmes  108. 22PH. 004  and  110. 249Y. 004. F. L. acknowledges the support by the  Deutsche Forschungsgemeinschaft (DFG ,  German Research Foundation)  -Project number  314665159. D. C. is supported by the  LMU-Munich Fraunhofer-Schwarzschild Fellowship  and by the  Deutsche Forschungsgemeinschaft (DFG ,  German Research Foundation)  under Germany's  Excellence Strategy   -EXC 2094 -390783311.
E. N. acknowledges the support by the  DFG Research Unit   FOR2544 "Blue Planets around Red Stars ". M. R. and S. C. acknowledge the support by the  DFG priority program SPP 1992  " Exploring the Diversity of Extrasolar Planets " ( DFG PR 36 24602/41  and  CZ 222/5-1 , respectively). D. S. acknowledges funding from project  PID2021-126365NB-C21 ( MCI / AEI/FEDER, UE)  and financial support from the grant  CEX2021-001131-S  funded by  MCIN/AEI/ 10. 13039/501100011033.
The datasets were chosen based on the simple, well-defined morphologies of the Si without addition of coatings or dopants. Two datasets consisting of GCD data from nanowires (NWs) and thin films (TFs) were chosen. This gave two avenues for exploration, namely, a morphology with controlled 2D diffusion radius and large surface area (the NWs), and a morphology with controlled 1D diffusion length and small surface area (the TFs). The suitability of the fitting method is validated and the meaning of the parameters is discussed to reveal the differences and similarities in the behaviour of Si in different morphologies. As a result, this methodology facilitates the analysis of the electrochemical data in greater details and the exploration of the contributions of multiple electrochemical processes.
5 C (16. 8 to 33. 5 µA/cm 2 ) in the range of 0. 05-1 V with regular diagnostic cycles after every 50 cycles. The diagnostic cycles consisted of one cycle at 0. 05 C, two cycles at 0. 2 (6. 7 to 13. 4 µA/cm 2 ), C, and two cycles at 0. 5 C. Cycling experiments were conducted at 25 °C in temperature-controlled cabinets (VWR INCU-Line) using an Arbin LBT battery tester. Fitting was performed in Python using the lmfit package.
This shows that the fitting function provides a powerful tool for analysing the behaviour of Si phases according to their component curves. As seen in Figure  2 , the behaviour of a parameter is affected by all other parameters and it is therefore difficult to separate their behaviour and ascribe meaning to them. Nevertheless, in order to show the changes in the datasets over time, the plots of the individual parameters α, c, s, γ, and w are shown in the SI. The differences in behaviour of the TFs and NWs shown in Figure  2  give insights into the behaviour of the materials, and can give information about how Equation (1) relates to physical phenomena occurring in the cells. For instance, the increased skewness seen in the phase I peak for TFs (Figure  2a ) indicates that there is a relatively large "lagging" effect as the potential increases faster than the diffusion can equilibrate.
This is consistent with the expectation that the delithiation is hindered by the long diffusion distance of Li to the surface of the Si. The less skewed phase I NW peak (Figures  2b  and S1a ) supports this hypothesis, as the thin NWs have lower diffusion lengths, and can diffuse Li in radial directions. The decrease in skewness factor α I seen when cycling the TFs at lower Crates (Figure  S1b ) further corroborates this, as cycling at rates closer to equilibrium would decrease the diffusion overpotentials. Similarly, the differences in phase position c I of phase I give information about two datasets. For thin films, the positions of phase I shift from around 270 to 250 mV over the course of cycling, while NWs show the opposite trend, with the position increasing from 250 to 300 mV. In both cases, however, the positions of c I (Figure  S2 ) are very close to the equilibrium potentials determined by the previous literature  [6, 42, 43].
As with phase I, analysis of phase II gives important information about the behaviour of Si. Notably, c I I is independent of TF thickness, and only slightly decreased at slower C-rates (Figure  S2b ), varying from 460 to 480 mV. Meanwhile, c I I (shown as diamonds on the curves in Figure  2 ) for the NWs shows a small shift from 460 to 500 mV at the start of cycling before reaching a steady state. This initial increase could be due to an increase in overpotentials due to SEI formation in early cycles. The shift to lower potentials seen in phase I is not reflected in phase II because the position of phase II is relatively close to the middle of the dataset. Hence, there are enough datapoints at low voltages to adequately describe the curve. While phase I is described only by the skew-Gaussian component (w = 1), phase II is described by a combination of both the skew-Gaussian and Lorentzian components.
Phases of Si Delithiation To further highlight the ability of this method to show differences between the datasets in ways that are not obvious by dQ/dV, the capacities of the two phases normalized to the total capacity determined by the fitting are shown in Figure  3. The horizontal dotted lines denote the initial guesses for the fitting of the phases as discussed in Section 3. 1. While this shows that the assumption made initially, i. e. , that the datasets consist of 100% Li 3. 5 Si at the start of delithiation and 100% Si at the end of delithiation, was not completely accurate, the fitting reveals interesting differences between the TF and NW samples. For both TFs and NWs, the first 10 to 20 cycles show an increase in the contribution to the total capacity from phase I. However, while phase I for the TFs contributes less capacity than expected throughout cycling, the capacity contribution from phase I for the NWs continues to increase and eventually exceeds the amount of capacity expected from the initial assumption made in Section 3.
Conclusions Two datasets of previously published data consisting of delithiation cycling data from a thin film and a nanowire study performed by different groups, were analysed using an empirical cumulative distribution function consisting of a skewed pseudo-Voigt. Both datasets featured Si half-cells cycled in the amorphous region of Si and the skewed pseudo-Voigt was applied to each of the two electrochemical phases Li 3. 5 Si (phase I) and Li 2 Si (phase II). The fitting function was found to give excellent fits to both datasets at C-rates far above equilibrium conditions, and was able to determine differences and similarities between the two morphologies studied. Phase I of the NW samples were found to be less skewed than the TFs, indicating faster delithiation. However, loss of contact between NWs and excess SEI growth also lead to increased resistances of the electrodes, in particular for the less electronically conductive phase II.
Acknowledgments: The authors acknowledge  Rasim Batmaz  and  Jørn Døvling of Beyonder  for their advice and many useful discussions. The thin film electrochemical experiments were funded by the  Research Council of Norway  through the  ENERGIX  Project No. 280985 , and performed within MoZEES, a  Norwegian Centre for Environment-friendly Energy Research  (FME), co-sponsored by the  Research Council of Norway  (project number  257653 ) and 40 partners from research, industry, and the public sector. The authors would also like to thank  Pascale Chenevier  for her advice on SiNWs.
Jones et al. 2023, in preparation). This paper is structured as follows: in Section 2 we present a description of the new MIRI/MRS observations and data reduction, in Section 3 we describe the mid-infrared properties of the core of M83, and in Sections 4 and 5 we present a discussion of the observed properties and a brief summary, respectively. As an initial note, we highlight that all of the molecular gas masses discussed in this work refer to the H 2 masses, with no heavy element correction.
Observations and Data Reduction The JWST observations presented in this paper were collected as part of Cycle 1 under PID 02219 (PI: Hernandez) between 2022 July 5 and 9. Given the expected pointing accuracy of JWST (∼0 10), the program did not require a target acquisition. The M83 observations were taken with the MIRI/MRS instrument to create a 2 × 2 mosaic, which fully sampled the entire nucleus of this nearby galaxy primarily with the largest MRS channel 4 (with a field of view (FOV) of 6 9 × 7 9 per pointing, see Figure  1 ). A 4 point dither pattern optimized for extended sources was also applied to achieve optimal sampling throughout the MRS FOV and to identify and remove detector artifacts. The individual pointings were strategically positioned to fully sample the massive stellar clusters with all four MIRI/MRS channels.
To avoid data excess problems the observations were divided into three separate visits, each observing with a different grating, SHORT (A), MEDIUM (B), and LONG (C), to obtain contiguous wavelength coverage from ∼5-28 μm. Each pointing was observed with 40 groups per integration for a total of five integrations and a total exposure time of 2264 s. Additionally, to accurately measure and correct for the thermal background, the program collected companion background MRS cubes avoiding contamination from the disk of the galaxy with identical integrations as those of the individual pointings. The MIRI/MRS raw products were retrieved from the Mikulski Archive for Space Telescopes (MAST). The observations were reduced with the JWST calibration software version (CAL_VER) 1. 6. 2. We also applied residual fringe corrections available in the JWST pipeline to both the threedimensional and one-dimensional observations, in the latter taking care of the low-level dichroic fringing pattern.