dataesr/scientific-paragraphs-categorization huggingface dataset:
Using WebPPL-an easy-to-learn PPL  9  -and Birch-a language with a more computationally efficient inference machinery  14  -we develop techniques that allow us to automatically generate efficient sequential Monte Carlo (SMC) algorithms from short descriptions of these models (~100 lines of code each). Although we found it convenient to work with WebPPL and Birch for this paper, we emphasize that similar work could have been done using other universal PPLs. Adopting the PPL approach allows us generate the first efficient SMC algorithms for these models, and the first asymptotically exact inference machinery for the full BAMM model. Among other benefits, SMC inference allows us to directly estimate the marginal likelihoods of the models, so that we can assess their performance in explaining empirical data using rigorous Bayesian model comparison.
Taking advantage of this, we show that models with slowing diversification, constant turnover and many small shifts (all combined in ClaDS2) generally explain the data from 40 bird phylogenies better than alternative models. We end the paper by discussing a few problems, all seemingly tractable, which remain to be solved before PPLs can be used to address the full range of phylogenetic models. Solving them would facilitate the adoption of a wide range of novel inference strategies that have seen little or no use in phylogenetics before.
The BAMM model has been implemented in dedicated software using a combination of MCMC sampling and other numerical approximation methods  17, 24. The implementation has been criticized because it can result in severely biased inference  18. To date, it has not been possible to provide asymptotically exact inference machinery for BAMM. In a recent contribution, a simplified version of BAMM was introduced: the LSBDS model  16. LSBDS is an episodic CRBD model, that is, it is equivalent to BAMM when z = 0. Inference machinery for the LSBDS model has been implemented in RevBayes  5  based on numerical integration over discretized prior distributions for λ and μ, combined with MCMC. The computational complexity of this solution depends strongly on the number of discrete categories used. If k categories are used for both λ and μ, computational complexity is multiplied by a factor k 2.
Such series of similar probability distributions are not available naturally in the MCMC algorithm, but have to be constructed in more involved, computationally complex procedures, such as thermodynamic integration  29, 30  , annealed importance sampling  31  , or steppingstone sampling  32. Using the SMC machinery, we then compared the performance of the different diversification models on empirical data by inferring the posterior distribution over the parameters of interest, and by conducting model comparison based on the marginal likelihood (Bayes factors). Specifically, we implemented the CRB, CRBD, TDB, TDBD, BAMM, LSBDS, and ClaDS0-ClaDS2 models in WebPPL and Birch. The model descriptions are provided at https://github. com/phyppl/probabilistic-programming. They are similar in structure to the CRBD program presented above.
Our verification experiments (Supplementary Note Section 7) suggest that the light-weight PPL implementations of ClaDS1 and ClaDS2 provide more accurate computation of likelihoods than the thousands of lines of code developed in the initial implementation of these models  15. Previous discussion on the relative merits of diversification models have centered around the results of simulations and arguments over biological realism  [15] [16] [17] [18] 38  , and it has been complicated by the lack of asymptotically correct inference machinery for BAMM  18, 38. Our most important contribution in this context is the refinement of PPL techniques so that it is now possible to implement correct and efficient parameter inference under a wide range of diversification models, and to compare their performance on real data using rigorous model testing procedures.
The PPL analyses of bird clades confirm previous claims that the ClaDS models provide a better description of lineage-specific diversification than BAMM  15. Even when simpler models have higher likelihoods, the ClaDS models seem to pick up a consistent signal across clades of small, gradual changes in diversification rates. Like many previous studies  39  , our analyses provide little or no support for extinction rates above 0. This might be due in part to systematic biases in the sampling of the leaves in the observed trees  40, 41  , a problem that could be addressed by extending our PPL model scripts (Supplementary Note Section 10. 6). Such sampling biases can also give the impression of slowing diversification rates even when rates are constant, potentially explaining some of the support for negative values of z and logα in our posterior estimates.
We want to emphasize, however, that there is a range of other possible explanations for these patterns  23. The idea that lineage-specific variation in diversification rates might be responsible for low estimates of extinction rates in analyses using simpler models  42, 43  finds little support in our results but we cannot exclude the possibility that even more sophisticated lineage-specific models than the ones considered here might provide evidence in favor of this hypothesis. An interesting observation is that models with constant turnover (as in ClaDS2) appear to fit empirical data better than those with constant extinction (as in ClaDS1), even though constant extinction has been commonly assumed in previous studies. A fascinating question that is now open to investigation is whether there remains evidence of occasional major shifts in diversification rates once the small gradual changes have been accounted for, something that could be addressed by a model that combines ClaDS-and BAMM-like features.
This would seem to touch on the major obstacles that remain. We then need to extend our current PPL models so that they also describe the nucleotide substitution process along the tree, and condition the simulation on the observed sequences. To generate the standard MCMC machinery for sampling across trees from such descriptions, delayed sampling needs to be extended to summarize over ancestral sequences (Felsenstein's pruning algorithm)  50  , and it should be applied statically through analysis of the script before the MCMC starts rather than dynamically. State-of-the-art MCMC algorithms for PPLs  12  must then be extended to generate computationally efficient tree samplers, such as stochastic nearest neighbor interchange  51. Applying SMC algorithms for sampling across trees  52  is even simpler, it just requires delayed sampling to summarize over ancestral sequences.
Methods PPL software and model scripts. All PPL analyses described here used WebPPL version 0. 9. 15, Node version 12. 13. 1  9  and the most recent development version of Birch (as of June 12, 2020)  14. We implemented all models (CRB, CRBD, TDB, TDBD, ClaDS0-ClaDS2, LSBDS, and BAMM) as explicit simulation scripts that follow the structure of the CRBD example discussed in the main text (Supplementary Note Section 5). We also implemented compact simulations for the four simplest models (CRB, CRBD, TDB, and TDBD) using the analytical equations for specific values of λ, μ, and z to compute the probability of the observed trees. In the PPL model descriptions, we account for incomplete sampling of the tips in the phylogeny based on the ρ sampling model  63. That is, each tip is assumed to be sampled with a probability ρ, which is specified a priori.
Inference strategies. To make SMC algorithms more efficient on diversification model scripts, we applied three new PPL inference techniques: alignment, delayed sampling, and the alive particle filter. "Alignment"  36, 64  refers to the synchronization of resampling points across simulations (particles) in the SMC algorithm. The SMC algorithms previously used for PPLs automatically resample particles when they reach observe or condition statements. Diversification simulation scripts will have different numbers and placements of hidden speciation events on the surviving tree (Fig. 2 ), each associated with a condition statement in a naive script. Therefore, when particles are compared at resampling points, some may have processed a much larger part of the observed tree than others. Intuitively, one would expect the algorithm to perform better if the resampling points were aligned, such that the particles have processed the same portion of the tree when they are compared.
This is indeed the case; alignment is particularly important for efficient inference on large trees (Supplementary Note Fig. 3 ). Alignment at code branching points (corresponding to observed speciation events in the diversification model scripts) can be generated automatically through static analysis of model scripts  36. Here, we manually aligned the scripts by replacing the statements that normally trigger resampling with code that accumulate probabilities when they did not occur at the desired locations in the simulation (Supplementary Note Section 6. 1). "Delayed sampling"  13  is a technique that uses conjugacy to avoid sampling parameter values. For instance, the gamma distribution we used for λ and μ is a conjugate prior to the Poisson distribution, describing the number of births or deaths expected to occur in a given time period.
Acknowledgements We thank  Lars Arvestad  and  Philippe Veber  for their contributions to the early development of the ideas presented here, and  Odile Maliet  for extensive help with the RPANDA implementation of the ClaDS models. This work was supported by grants from the  Swedish Research Council  to J. B. and J. K. (No. 2013-4853 ) and to F. R. (No  2018-04620 ), by the  Swedish Foundation for Strategic Research (SSF)  via the project " ASSEMBLE " (Contract No. :  RIT15-0012 ) to T. B. S. , D. B. , and J. K. , and by the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie  grant agreement PhyPPL No. 898120  to V. S. The computations were performed on resources provided by the  Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC).
, 2012; Célini et al. , 2020). Salt structures of the Digne Nappe region were both related to downbuilding in thick salt area, as well as reactive structures initiated by the Tethyan Liassic rifting. Most of them were still active during the early passive margin stage, and continued to evolve during the whole Alpine history. They played an important role during Alpine compression by accommodating shortening  (Graciansky et al. , 1986; Dardeau and Graciansky, 1990; Dardeau et al. , 1990; Graham et al. , 2012; Célini et al. , 2020). The evolution of salt structures observed in the field is usually, by necessity, depicted through cross-sections a 2D/ time perspective only. Offshore, 3D seismic datasets allow a real 3D/time investigation of the salt structures and associated depocenters. (Rowan et al.
This database is a geological and geochronological compilation made to study a small Archean/Paleoproterozoic block located in the centre of the Precambrian rock exposition of Uruguay. Petrographic and field outcrops data supporting the samples from which the zircons for textural analysis and U-Pb dating (LA-ICP-MS) come are presented at first with their descriptions. The first table (1) contains the new U-Pb isotopic data. The second table (2) presents a correlation of textures from different zircon samples. The last table (3) contains an inventory of different U-Pb ages found in antecedents. All these data are associated with the paper entitled: "The Archean Pavas Block in Uruguay: extension and tectonic evolution based on LA-ICP-MS U-Pb ages and airborne geophysics".
Acknowledgments We are indebted to the Director Lic. Nestor Campal authorised the use of the airborne geophysical data of DINAMIGE for academic purposes. We also thank  Bruna Sanches ,  Nairé Gabriel , and the rest of the team at the  Centro de Pesquisas Geocronologicas of the University of São Paulo. We thank  Dr Elena Peel  for the help regarding the use of standard deviation in the Concordia diagram. The authors are grateful to  CSIC ( UdelaR)  for the funding granted (first author's project  CSIC-2015 C-604  ) and to the  Faculty of Sciences of the Universidad de la República (Uruguay)  for the Logistics. They also acknowledge  PEDECIBA -Geosciences , who provided third author's grants. To Ecos-sud Conicyt program n  °U17U01  for funding the travels and per diem to  Tahar Aïfa  and  Henri Masquelin  through a cooperation exchange program between the Rennes 1 and  UdelaR  universities since 2018.
Methods Original field structural surveys along with remote sensing analysis were performed to characterize the regional-scale pattern of tectonic lineaments (i. e. , faults and shear zones) and dykes in the study area (20-km wide, 50-km long). Remote sensing analysis was performed using satellite images (i. e. , Sentinel-2, Google Earth and Bing) as reference maps coupled with published geologic and structural maps  (Cembrano et al. , 2005; Domagala et al. , 2016; González & Niemeyer, 2005). Six representative localities along the BFZ and two along the CCSZ were selected for a detailed analysis (Figures  2  and 3 ). At each locality, we used a DJI Phantom 4 Pro drone to take nadir-directed aereophotographs. The images were processed in Agisoft Metashape Professional software to generate high-resolution georeferenced orthomosaics (spatial resolution of ∼10 cm/pixel) used as base maps for the surveys at 1:300, 1:500, or 1:1,000 scale.
Tectonics kinematics of the different structural elements (magmatic foliations, dykes, joints, faults, and ductile shear zones) were systematically measured and digitalized using ArcGIS 10. 6 software. Structural measurements (n = 2,716) were plotted onto stereonets (equal area, low hemisphere) using Stereonet 10  (Allmendinger et al. , 2011; Cardozo & Allmendinger, 2013). Oriented rock samples (n = 178) were collected for microanalytical investigations. Microstructural observations were conducted on polished thin sections (n = 60) oriented parallel to the X kinematic direction (stretching lineation and slickenline in shear zones and faults, respectively) and orthogonal to the X-Y plane (shear zone boundary and fault plane). Transmitted-light optical microscopy (OM) was used to determine microstructural features at thin-section scale and to identify areas suitable for microanalytical investigations.
Mineral composition of main mineral phases was obtained by electron wavelength-dispersive microprobe analysis (EMPA). EMPA investigations were performed with a Joel-JXA8200 microprobe equipped with EDS-WDS (5 spectrometers with 12 crystals), installed at INGV-Rome, and a Cameca SX50 microprobe, installed at the Department of Geosciences (Padova). Data were collected using 15 kV as accelerating voltage and 7. 5 nA as beam current. A slightly defocused electron beam with a size of 5 μm was used, with a counting time of 5 s on background and 10 s on peak. Albite (Si, Al, and Na), forsterite (Mg), pyrite (Fe), rutile (Ti), orthoclase (K), and apatite (Ca and P) were used as standards. Sodium and potassium were analyzed first to prevent alkali migration effects. The precision of the microprobes was measured through the analysis of well-characterized synthetic oxide and mineral secondary standards.
Acknowledgements This work is supported by  FRQNT  (nouveaux chercheurs, Grant No. 174726 , Equipe  2016-PR-189974 ), the  National Sciences and Engineering Research Council of Canada (NSERC)  ( Discovery Grant   RGPIN-2018-05772  and the  Alexander-Graham-Bell Graduate Scholarship  for S. V. ),  Compute Canada  (Job: pve-323-ac) as well as the  Canada Foundation for Innovation (CFI). This study has also received financial support from the  French National Research Agency (ANR)  in the frame of "the Investments for the future"  Programme IdEx Bordeaux- ANR-10-IDEX-03-02 , from the  Swedish Research Council (VR)  and the  Knut and Alice Wallenberg Foundation (KAW). Concerning the use of the  Lund Laser Center , we acknowledge support by  Laserlab Europe  (Grant Agreement 654148 under the European Union's  Horizon 2020 research and innovation programme ).
Data For a real data application of the conversion technique, eight local earthquakes are used. These were recorded by three dark ocean-bottom telecommunication cables deployed in the Mediterranean Sea. This dataset is identical to the one used by  Lior et al. (2021) , and the cables' locations, bathy-metric profiles and layout are detailed there. This information, as well as earthquake data, is briefly repeated here. Data were acquired by Géoazur on two cables deployed offshore from Methoni, southwestern Greece, and one cable deployed offshore from Toulon, southern France. In addition to DAS data, several on-land seismometers, installed near the cables, were available during the measurements. These will be used later (Sect. 6) to compare DAS, and seismometerderived source parameters. The earthquake data are detailed in Table  1 ; earthquakes, cables and seismometer locations are shown in Appendix A; and magnitude and hypocentral  distance distribution are shown in Fig.
6. In the latter, variations of hypocentral distance correspond to the different analyzed fiber segments. The earthquake DAS records used in this study are dominated by scattered Scholte waves, with velocities between 100 and 400 m s -1  (Lior et al. , 2021). The two cables deployed offshore from Greece are used for the HCMR (Hellenic Centre for Marine Research) and NESTOR (Neutrino Extended Submarine Telescope with Oceanographic Research) projects. The acquisitions were conducted on 18 and 19 and 19-25 April 2019 on the HCMR and NESTOR cables, respectively. A Febus A1 DAS interrogator was used, measuring strain-rate signals. Data were sampled at 6 and 5 ms for HCMR and NESTOR, respectively, and gauge length and spatial sampling were both set to 19. 2 m for both cables. These records amount to 688 and 1365 equally spaced channels for the 13.
Code and data availability. Simulated and observed DAS earthquakes are available on https://osf. io/98cnk/ (last access: 15 January 2021) and https://osf. io/4bjph/ (last access: 27 December 2020), respectively. Broadband seismometer data were acquired by Géoazur; data for the POSAN and POSAS stations were downloaded from RESIF (http://seismology. resif. fr/, (last access: 1 May 2020).
Acknowledgments. G. M, J. M. , E. D. , and  J-M. C. thankfully acknowledge support from the  National Science Foundation Division of Polar Programs  under Awards  1603557  and  1543366. C. L. , H. R. , and C. T. thankfully acknowledge support from the  French ANR  through the project  ImMEDIAT  under Award  ANR-18-CE01-0010. P. E. I. was partially funded by the  KeyClim  project, funded by the  Research Council of Norway  ( Award 295046 ). Our collaboration has been made possible by funding from the  MIT-France MISTI Global Seed Funds  for the project '' The Arctic in a Warming World. ''The Pan-Arctic simulation was performed using HPC resources from  GENCI-CINES , Award  2018-A0050107420. Data availability statement. Mooring data were collected and made available by the  Beaufort Gyre Exploration Program  based at the  Woods Hole Oceanographic Institution  (https://www.
They also showed that the deviation of the CLD from the exponential law, which can be calculated using µ 2 , varies with snow types. However, no measurement of snow optical properties was used in this study to evaluate the validity of their findings. To sum up, it has been shown that BRF, especially in high absorptive wavelengths, is more sensitive to snow morphology than snow albedo (bi-hemispherical reflectance). Yet no clear relationship has been either established theoretically or evaluated experimentally using optical measurements combined with an objective quantification of the snow microstructure. The objectives of the paper are thus to (i) describe one of the very few datasets that combined measurements of the bidirectional reflectance over the 500-2500 nm range and X-tomography characterization of the snow microstructure, (ii) evaluate the accuracy of the model of  Malinka (2014)  to simulate the snow BRF and its dependencies on snow microstructure parameters, and (iii) investigate the relationship between bidirectional reflectance and the snow microstructure beyond SSA using both simulation and measurement.
Experimental set-up and sample description The general idea of the experiment was to characterize both the snow microstructure and the BRF for the same macroscopic snow sample. The dataset consisted of three macroscopic snow samples: S1 analysed in March 2012 and S2 and S3 analysed in March 2013. S1 consisted of decomposing and fragmented particles/rounded grains (DF/RG) according to the classification of  Fierz et al. (2009). S2 was composed of faceted crystals/depth hoar (FC/DH) obtained in a temperature gradient experiment. S3 was taken from the same temperature gradient experiment as S2 except that it was turned upside down so that the grain orientation was changed by 180 •. Under temperature gradient, the facet formation is oriented toward the warmer side of the snow layer. For instance, when the temperature gradient is pointing downward, as is usually the case in nature, the facets tend to form on the downward surfaces while the upward surfaces stay more rounded (see e.
To examine this effect, we simulate the snow reflectance in the most pronounced difference range 1400-1900 nm using the values of the complex refractive index of ice taken from different databases. Figure  10  compares the measured and the simulated reflectances in this range for S1 and S2, using several databases of the complex refractive index of ice:  Warren (1984) ,  Kou et al. (1993) ,  Grundy and Schmitt (1998) , and  Warren and Brandt (2008). For S1 both the incidence and observation angles are 60 •. For S2 the observation angle is 60 • , but the incident angle is taken as 30 • , because of the problems discussed in Sect. 3. 2. As seen from Fig. 9 , the data from Grundy and Schmitt (1998) provide the simulated values closest to the measured ones and will be used in further simulations for this spectral region.
Discussions and conclusions This study presents a dataset that combines the snow bidirectional reflectance over the 500-2500 nm range with different illumination geometries and 3D images of snow using X-ray tomography, which allows analysis of the snow microstructure, e. g. its SSA and density. The SSA is calculated using two different methods: the voxel projection method (VP) and the method based on the ice chord length distribution (CLD). The comparison between the two SSA values is in excellent agreement (R 2 = 0. 994). The SSA and mean chord values computed from 3D images are generally lower than those obtained via DUFISSS and ASSSAP optical methods and in excellent agreement with those re-trieved via spectral albedo. The comparison between density values obtained via the 3D images and via manual measurements exhibits slightly higher density for 3D images, which might relate to the heterogeneity of the samples and to the segmentation process applied to the images (see Fig.