dataesr/scientific-paragraphs-categorization huggingface dataset:
Reference datasets used for proteomics data analysis Publicly available reference sequences for molluscs are far from abundant, given the size of the phylum. Most of the proteomic studies on bivalve nacre proteins have been carried out on sub-class Pteriomorphia and very limited informations is known of other nacre bearing bivalves such as freshwater pearl mussels  (Marie et al. , 2017). We performed two separate searches for each sample, using: The Protein database nominally includes a large number of species (e. g. more than 3000 bivalves), but only a few organisms are represented by a significant number of sequences (e. g. the marine bivalves Crassostrea gigas, Mizuhopecten yessoensis, Crassostrea virginica, Mytilus galloprovincialis, Pinctada fucata). The top-thirty freshwater bivalves represented in this database are (the number of sequences in brackets): Cumberlandia monodonta (561), Popenaias popeii (496), Potomida littoralis (357), Elliptio hopetonensis (269), Dreissena presbensis  (200), Cyprogenia aberti (198), Elliptio dariensis (197) , Elliptio icterina (182), Obovaria jacksoniana (158), Unio tumidus (129), Anodonta anatina (105), Corbicula fluminea (101), Unio delphinus (99), Margaritifera falcata (98), Toxolasma parvus (97), Pyganodon grandis (97), Hyriopsis cumingii (95), Unio mancus (89), Utterbackia imbecillis (89), Utterbackia peninsularis (86), Lampsilis cardium (84), Strophitus radiatus (84), Unio elongatulus (82), Quadrula pustulosa (76), Venustaconcha ellipsiformis (73), Sinanodonta woodiana (67), Anodonta cygnea (62), Unio crassus (61), Elliptio complanata (60).
However, the sequences are usually not relevant to the shell or the shell mantle: for example, all 61 Unio crassus sequences refer to two proteins: cytochrome oxidase subunit I and NADH dehydrogenase subunit. The EST sequence database contains 75 molluscan species (25 gastropods, 38 bivalves, eight cephalopods, 2 polyplacophorans and two shell-less molluscs). For bivalves, the EST sequences include well-studied pearl-producing species, most of which belonging to the Pterioida order (Pinctada sp. ), but also the edible oyster and the mussel (Ostreoida and Mytilidae sp. ). Only 2 EST sets correspond to freshwater bivalves: Lamellidens marginalis (native to southeast Asia) and Hyriopsis cumingii (commonly known as Triangle Sail Mussel, native to China and Vietnam), both belonging to order Unionoida.
Peptide and protein identification Product ion spectra of reference shells and archaeological double-buttons were analysed using PEAKS  Studio (v. 8. 5, Bioinformatics Solutions Inc (BSI) ;  (Ma et al. , 2003)  and searched separately against the Mollusca Protein and Mollusca EST databases, including the search of common laboratory contaminants (cRAP; common Repository of Adventitious Proteins: http://www. thegpm. org/crap/). Search parameters were defined assuming no enzyme digestion, fragment ion mass tolerance of 0. 05 Da and a parent ion tolerance of 10 ppm. Results obtained by SPIDER searches (i. e. including all possible modifications) were used for peptide identification and protein characterization, choosing the following threshold values for acceptance of high-quality peptides: false discovery rate (FDR) threshold 0.
Results Table  2 -source data 1 summarizes the main proteins identified in the reference shell samples and the double-buttons, grouped by taxon. Here we include a brief overview of several freshwater shell 'specific' matrix proteins detected in our samples:. Hic74 (GenBank: ARG42316. 1) is an acidic (IP 4. 68), alanine and glycine rich matrix protein, supposedly involved in nacreous layer formation  (Liu et al. , 2017a). Its structure consists of poly-alanine blocks (at least 17) with short acidic motifs, a 'GS loop' type coil structure of lustrin A  (Wustman et al. , 2002)  at the C-terminus, the C-terminal 30 residues of which consist of short acidic-basic motifs. It is probably a structural, silk-like protein, providing mechanical function (a system that dissipates the cracks) with short acidic sites to bind the mineral.
Hic52 (GenBank: ARH52598. 1) is a very basic (IP 10. 82), glycine (almost 29%) and alanine rich protein. It has poly-glutamine and poly-glycine blocks with several degenerate repeats of different lengths along the sequence. It was reported to have collagen-like structure  (Liu et al. , 2017b)  and probably plays a structural role in nacre formation. Silkmapin (GenBank: AIZ03589. 1) and its isoforms (nasilin 1 and 2 (GenBank: ASQ40996. 1 and ASQ40997. 1)) are glycine-rich (>34%), non-acidic proteins with a structural function and probably play a role in the deposition of both nacre and prismatic layers  (Liu et al. , 2015). Chitin deacetylase enzyme (present in isoforms A and B (GenBank: AFO53262. 1 and AFO53263. 1)) is a slightly basic (IP 8. 34) protein, with a chitin deacetylation function and possibly has a role in the 3D structuring of the mineral framework.
Carbonic anhydrase 3 (Hyriopsis cumingii, GenBank: ARG42317. 1) is an asparagine (10. 2%) and threonine (9. 3%) rich, acidic (IP 5. 9) protein. The active enzymatic domain comprises most of the sequence, except for the C-terminal 40 residues, which have completely biassed amino acid composition, enriched in asparagine and acidic residues. This protein is typical of a CA associated to calcium carbonate biominerals, as it possesses a supernumerary low complexity domain (Le  Roy et al. , 2014) , which would promote the binding of the enzyme onto the mineral surface.
The same analysis was repeated for the seven archaeological double-buttons and the results are presented in Appendix 1-figure 24. Searching against the EST database, the Havnø samples yielded the highest number of identified sequences (as can be seen in the figure, more than two thirds of the circular area is occupied by Havnø). While the highest degree of closeness was observed within the the same set of samples (Havnø and Hornstaad), a degree of similarity was also observed between the three different sets. This was particularly evident for HavA, which shared sequences not only with HavB and HavC, but also with all the three Hornstaad samples and with PesB. In the Hornstaad double-buttons we observed a lower amount of identified EST sequences and a more limited extent of similarity between sample sets.
Database independent biomolecular comparisons The classification of samples on a molecular level has been widely applied for phylogenetics to study the evolutionary relationships between species. However, database-dependant search algorithms of DNA and/or protein sequences cannot take into account peptides and proteins that do not yet exist in databases. In recent years, as shotgun proteomics has become a routine tool for biochemistry, and huge amounts of data have been generated on novel systems and organisms (including extinct), there has been an increasing interest in developing methods enabling to compare proteome-wide measurements that would be flexible and allow database-free workflows  (Palmblad and Deelder, 2012; Rieder et al. , 2017; Yılmaz et al. , 2016).
Peptide sequence similarity The peptide sequences generated by de novo algorithm of the software PEAKS Studio 8. 5 (Bioinformatics Solutions Inc) were used in a database-independent biomolecular comparison. Any peptides belonging to contaminants were removed prior to the analysis, by searching each sample against a common laboratory contaminant database (cRAP; https:// www. thegpm. org/crap/). The lists generated by this analysis contained peptide sequences reconstructed by the PEAKS software on the basis of the raw product ion spectra. Only common post translational (phosphorylation) and diagenesis-induced (deamidation, oxidation and dioxidation, pyro-Glu formation) modifications were taken into account by the PEAKS algorithm. Each sequence is present only once (unique), thus the number of peptide sequences does not affect the overall analysis.
Proteome wide distance calculations based on product ion spectra We attempted to perform comparative shell proteome analysis based solely on the proteome-wide distance calculation of different product ion spectra using a DISMS2 algorithm implemented in R language  (Rieder et al. , 2017). The algorithm is a four-step procedure, consisting of spectra filtering, checking constraints for matching, matching of product ion spectra and calculation of the distance matrix with pairwise distances between runs. Raw data of each sample were processed using PEAKS Studio 8. 5 (Bioinformatics Solutions Inc) -searched against a common laboratory contaminant database cRAP (https:// www. thegpm. org/crap/) to eliminate the possibility of matching contaminant spectra among the different samples. The exported de novo only peptide spectral data were converted to mzXML format using ProteoWizard and used directly as a primary input in R.
The PesB sample falls in the middle, not showing a clear and evident proximity to one particular sample, suggesting phylogenetic distance or alteration of the sample, coherently with chiral amino acid data (Appendix 1-figure  8 ) and all other databasedependant analyses. Overall, the consistent pattern revealed by database-dependent and database-independent protein data analysis as well as chiral amino acid analysis (these were all performed in the same laboratory in York) strongly support a biological effect (phylogenetic or diagenetic) and not an analytical effect for the clustering. Appendix 1-figure 25. Pairwise MS/MS comparison of the seven archaeological double-buttons and six reference shells (freshwater and marine): the cluster dendrogram is obtained from a distance matrix from proteome-wide distance calculations of product ion spectra implemented in R using the DISMS2 code.
Acknowledgements The authors are sincerely grateful to  Peter Rowley-Conwy  and two anonymous reviewers, as well as the Reviewing and Senior Editors, for exceptionally clear, valuable and insightful comments on this manuscript. BD and JS would like to thank  Rosa Boano ,  Cristina Giacoma ,  Massimo Maffei ,  Nadia Barbero  and their teams at the  University of Turin. JS and FM would like to thank  Justine Briard  (uB-FC) for help with sample preparation and  Emmanuel Fara  (uB-FC) for valuable insights and comments. BD, FM and JS are grateful to  Matthew Collins  ( Universities of Copenhagen and Cambridge ) and  Harry Robson  ( University of York ) for useful discussion. BD is supported by the  Italian 'Ministero dell'Istruzione dell'Universitae della Ricerca ' (Programma per  Giovani Ricercatori 'Rita Levi Montalcini ') and wishes to acknowledge the  Department of Archaeology at the University of York (UK)  and the  EU   FP7 Re(In )tegration grant  PERG07-GA-2010-268429  (project: mAARiTIME) for funding pilot research.
JS, BD and FM are also supported by the  PHC Galilee programme, Italo-French University (UIF/ UFI ; project  G18À464/39612  SB) and JS acknowledges the support of  MIUR  and of a BGF funded by the  French embassy in Italy. The work performed at  UMR CNRS 6282 Biogeosciences (JS, BD, FM ), Dijon was financed via the annual recurrent budget of this research unit. KP acknowledges the support of the  Leverhulme Trust ,  PLP-2012-116. LP thanks the  CNRS (France)  and the  University of Bourgogne Franche-Comte(France). GM is supported by  'Ricerca Locale Universitadi Torino '. CT would like to thank  Stephanie Devassine ,  Fabrice Bray  and  Christian Rolando  ( MSAP, University of Lille ) for their technical contribution for MS operation. CT also thanks the  Institut Universitaire de France , the  European community (FEDER) , the  Region Hauts de France , the  IBISA network , the  CNRS , the  University of Lille  and the  FR 3624 FT-ICR.
12) : It  [was]  generally [considered to be] safer to select an experimentally reversed univariant equilibrium in a chemical subsystem that is buffered by mineral assemblages in the rock under study  […]  than to rely quantitatively on complex petrogenetic grids. At the same time,  Spear (1989)  was introducing the concept of relative thermobarometrybased on differential forms of the equilibrium constants, a variant of the Gibbs method  (Spear 1988). This original approach, if based on an internally consistent database (e. g. Berman 1988; Holland & Powell 1988 , 1998 , 2011) , permits the production of isopleth maps of mineral compositions, moles and equilibrium constants for a given bulk-rock composition, as well as forward models along P-T trajectories predicting the growth zoning of metamorphic minerals (see  Spear 1989, fig.
3c). Since that time, isopleth thermobarometry has become a powerful aid in the interpretation of complex reaction histories and mineral zoning  (Evans 2004; Tinkham & Ghent 2005; Gaidies et al. 2008; Moynihan & Pattison 2013; Lanari et al. 2017). This major development is being used routinely in modern petrological studies as isopleth maps can be readily obtained within a couple of minutes (or hours) for simple (and complex) rock systems and any thermodynamic database using a Gibbs energy minimizer such as Theriak-Domino (de Capitani & Brown 1987; de Capitani & Petrakakis 2010) or Perple_X  (Connolly & Kerrick 1987; Connolly 2005) , or using a phase-equilibrium calculator such as Thermocalc  (Powell & Holland 1988 , 2008)  or Gibbs   (Spear 1988). In his paper,  Tropper (2018)  uses an unconventional method to determine the accuracy of the phase diagrams.
2011; Carlson et al. 2015; Lanari & Engi 2017; Spear & Pattison 2017; Lanari & Duesterhoeft in press). Geochemical data: from small to large datasets Another important change in metamorphic studies is related to the amount and quality of geochemical data available in present-day research. The number of analytical instruments (scanning electron microscopy (SEM), electron probe microanalyser (EPMA), Raman spectroscopy, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), secondary ion mass spectrometry (SIMS/SHRIMP), Fourier transform infrared spectroscopy (FTIR), etc. ) and their increasing precision fundamentally changed the way petrologists and geochronologists deal with the available geochemical information to investigate rocks and their metamorphic history. We estimate that the total number of EPMA analyses used in the 55 chapters of the book from  Daly et al.
(1989)  to be around 2000, among which only  Burton et al. (1989)  reported core to rim compositional zoning profiles of two garnet grains. Between 40 and 50 Ar-Ar or K-Ar spectra, laser and spot analyses by SIMS were reported in the entire book. Today, the situation has changed dramatically in that much larger datasets are used to support models and interpretations. Many petrological studies include, for instance, core to rim compositional zoning profiles combined with semi-quantitative X-ray maps, providing a more detailed investigation of the compositional variability of minerals. Nowadays, X-ray maps can be quantified (calibrated like single-spot analysis), allowing the compositional variability of mineral phases to be analysed continuously in two dimensions. In their paper,  Lanari et al.
(2018)  show how quantitative compositional mapping has impacted mineralogical and petrological studies over the past half-century. The authors present a new calibration technique for electron probe microanalyser (EPMA) X-ray maps, which has been incorporated into the computer software XMapTools  (Lanari et al. 2014). Such data visualization tools are important as a set of maps typically contains between 200 000 and 1 000 000 spatially resolved fully quantitative chemical analyses. This paper by  Lanari et al. (2018)  illustrates how technological evolution has caused an exponential increase in the amount of data available and also shows how important the tools facilitating data processing and data handling are. It is not only the quantity of data that is important, but also the quality of the reporting and the analysis.
Are more high-resolution data improving our geological understanding of metamorphic rock evolution? Of course, it depends on the quality of the data and our capability to interpret this geological record. Two papers illustrate how large geochemical datasets are used to decipher the metamorphic evolution. The first example is presented in the article by  Martin (2018) , who uses quantitative compositional X-ray mapping to investigate the compositional variability of symplectite assemblages in eclogite from the Western Gneiss Region of Norway. This large geochemical dataset (corresponding to several million point analyses), used in conjunction with multiequilibrium models, enabled the P-T conditions of symplectite formation to be unravelled and the influence of external fluid on the progressive retrogression of mafic eclogite to be discussed.
Such magmatism coupled with collisional metamorphism is analogous to modern plate tectonic settings. One of the next challenges for the geodynamicists is the analysis of large metamorphic datasets. Integrating the large variety of petrochronological data into consistent tectonic and geodynamic models can strengthen our understanding of the formation of metamorphic belts. In the paper by  Oh & Lee (2018) , the authors have tracked the systematic changes in the metamorphic record and the distribution of the post-collisional igneous rocks along the Permo-Triassic Qinling-Sulu-Odesan belt located between the North China Craton and South China Craton. The authors have interpreted the variation in the peak-pressure conditions along the belt as being a result of the geometry of the continental margin.
Acknowledgements We would like to sincerely thank all of the authors for their hard work in writing and correcting the papers within the tight deadlines imposed by the editors. The success of this book weighs heavily on their shoulders and we are grateful for that. The authors were assisted by the constructive criticism and excellent recommendations of the reviewers; we acknowledge all of them for their work. We would like to thank  Jo Armstrong , our production editor, who is responsible for the exceptional quality of the final papers. The inspiration of this book comes from the organization by the editors of four sessions beginning in 2014 during the  General Assembly of the European Geoscience Union (EGU) in Vienna. We are grateful to the presidents of the GMPV Division,  Nick Arndt  and  Mike Burton , for their guidance through these years.
Breeding populations We used updated national population sizes and their recent trends  (9) , benefitting also from the recent reporting of EU members on Article 12 of the Birds Directive. Further updates were necessary not only for non-EU members but also for Poland, which previously published erroneous figures [see the Supplementary Materials and  (19) (20) (21) (22) ]. We combined these national population sizes with data on isotopic and genetic flyway assignments to estimate the total numbers of individuals using each flyway. For routes along the western flyway, we proposed three scenarios based on the proportions of logger-equipped males of each country using the Atlantic or the Mediterranean route (see the Supplementary Materials and data file S1). Field work included capturing males on their breeding territories, sampling one tail feather and three to six body coverts (scapulars), and equipping a sample of males with light loggers.
The colors depict the IUCN Red List status of the population as estimated from maximum extinction probability after 10, 20, and 100 years and three and five generations (see Materials and Methods for details; green, Least Concern; orange, Vulnerable; red, Endangered). In the best demographic scenario, the extinction risk is predicted to drop from 100 to 66% if 15,000 additional buntings survive the fall or to only 15% if 30,000 additional buntings survive the fall migration. Photo credits: S. Minkevicius. 1 year or more. Seized birds were sampled (one tail feather; n = 274) when being ringed at the care center just before being released in the wild. We divided feather data from these seized birds in three groups: (i) first-calendar-year individuals (n = 34; aged using a combination of molt contrasts, body feather streaking, and characteristic pointed tail feathers; these birds hatched in the year, so in September, they have retained feathers grown in the wild in the summer at their hatching site), (ii) attested decoys [n = 21, feathers grown in captivity, including all individuals with coloration anomalies (one or more white secondary or primary, fuliginous body coverts; this sample also includes one male kept in a care center for more than 1 year)], (iii) and unknown status (n = 179; which should be a mix of nonobvious decoys and wild recently captured adults).
In this species, autumn birds either have tail feathers grown in the nest (for juveniles) or molted on the breeding grounds before the fall migration (for adults). We therefore used samples collected from migrating individuals in France in August to September (in 4 years, 2012-2015; n = 40) and samples collected from seized first-calendaryear individuals (n = 34), while we also did the same analysis with samples collected along the eastern flyway in Kuwait in September 2014 (n = 78). In separate assignments to origin using  2 H f , potential origins for birds caught along the western (n = 74) and eastern (n = 45) flyways were restricted to their respective breeding areas on either side of the longitudinal migratory divide following political borders, based on results from geolocation data and genetic structure of breeding populations.
Archival light loggers Light loggers are small electronic devices that record light intensity, which, if retrieved after a migration cycle, enables the calculation of the approximate position of the logger given the duration of the day and the time of solar noon, both depending on latitude and longitude for a given calendar day. Geolocators do not remotely transmit positions; therefore, tags must be retrieved to download data. This necessitates animal recapture and, thus, site fidelity at wintering, breeding, or stopover locations. We used data collected by SOI-GDL 3. 0 (Swiss Ornithological Institute, 0. 65 g) and INTIGEO P65C2-7 (Migrate Technology, 0. 74 g) loggers, fixed with an ultraviolet-proof leg-loop string harness to the bird's back. The device and associated attachment material represent 3.
1 to 3. 5% of a bird's weight, a male ortolan bunting weighing on average (±SD) 21 ± 2 g during the breeding season. Colleagues from Sweden also successfully deployed Intigeo P65C2-7 loggers and previously published a large part of their tracking results  (26). We reanalyzed the raw data of tracks from nine individuals, corresponding to 11 migration tracks (two individuals were tracked during two migration cycles); the tracks obtained in 2015 were not published previously. We reanalyzed these data with similar parameterizations as for the other data. We also successfully deployed 18 Intigeo P65A9-10 longpin loggers in Germany. They provided tracks of 17 individuals, corresponding to 19 migration tracks (one individual fit in 2013 and in 2014 and another individual fit in 2013 and retrieved in 2015).
Two loggers stopped recording light data during the winter, two failed during the spring migration, but all provided autumn tracks. Overall, we retrieved 61 loggers (table  S1 ), 57 of which recorded data: Belarus (n = 1), France (n = 1), Russia (n = 14), Lithuania (n = 1), Finland (n = 8), Norway (n = 1), Poland (n = 2), Spain (n = 2), Sweden (n = 9), and Germany (n = 18). Three loggers (two from Sweden and one from Germany) provided data for two annual migration cycles, so we obtained 60 available autumn migration tracks. All retrieved INTIGEO loggers contained complete data for the period carried. Eleven SOI loggers were recorded from May until early August to early October 2015, so they provided partial migration tracks. Four more SOI loggers failed within a couple of weeks. We used the GeoLight 2.