dataesr/scientific-paragraphs-categorization huggingface dataset:
Errors. Despite the fact that the IBCAO Ver. 4. 0 DBM is a substantial improvement over previous versions, it is certainly not free of errors. The DBM remains limited by its underlying source database. The uncertainties associated with the depths of grid cells depend on a variety of factors including the approach used to correct soundings for sound speed, vertical referencing, navigation, and echo-sounder uncertainties. In addition, the gridding process will affect the final depth assigned to each grid cell. The random error component is thus a difficult parameter to derive, primarily because of lack of metadata on the widely varying data sources and the fact that some contributions are in the form of gridded compilations. In several areas we still rely on digitized contours from published maps for which the underlying source data are unknown.
While the random error component of DBMs have been estimated using statistical modeling approaches  41, 42  , we do not provide this for IBCAO Ver. 4. 0 because the metadata are not sufficient to provide a classification to a large enough portion of the database. Instead, the accompanying TIDs and SIDs provide information that is useful for users when addressing the reliability of IBCAO Ver. 4. 0. In addition, we have assembled two grids aimed to further assist users in assessing the reliability of the DBM: minimum and maximum depth grids. These grids report the minimum and maximum depth value for each grid cell, implying a depth range where the block median filter had several input depth values in one grid cell.
Usage Notes The most common uses of the IBCAO DBM are map-making and/or geospatial analyses using GIS software and other tools capable of displaying geographic information. The DBM is provided in netCDF and GeoTIFF formats, which are readily imported into most standard GIS software, for example QGIS and ArcMap. The 'x' and 'y' variables within the netCDF/GeoTIFF grid files represent the grid cell positions, along the x and y axis, in Polar Stereographic projection coordinates (meters), with a true scale set at 75°N. For the DBM, the 'z' value represents elevation in meters, depths below the sea surface are negative and heights above the sea surface are positive. The horizontal datum for the dataset is WGS 84 and the vertical datum can be assumed to be Mean Sea Level (however, note that there may be vertical reference issues for older observations, which may be due to chart datum).
For the TID grid, the 'band 1' value represents the TID code, describing the type of data on which the corresponding cell in the DBM grid is based. A list of TID codes is given in Table  1. The projection parameters are provided in the European Petroleum Survey Group (EPSG) database (https://epsg. io/) as code 3996. This database is used by standard GIS software implying that searching for EPSG 3996, or IBCAO, will provide the correct projection and datum for the IBCAO DBM. The Polar Stereographic coordinates can be converted to geographic using the GMT command mapproject with the following parameters: mapproject [input_lonlat] -R-  coordinates is achieved by adding -I to the command above. See http://gmt. soest. hawaii. edu/doc/latest/mapproject. html for more information. The GDAL command gdaltransform can also be used to convert between the Polar Stereographic and geographic coordinates by calling for the EPSG codes 3996 (IBCAO Polar Stereographic) and 4326 (WGS 84 geographic): gdaltransform -s_srs EPSG:4326 -t_srs EPSG:3996 The inverse conversion is simply achieved by swapping the order of the EPSG codes.
4. 0 Grid for any particular use. The IBCAO Ver. 4. 0 Grid is based on bathymetric data from many different sources of varying quality and coverage. As the IBCAO Ver. 4. 0 Grid is an information product created by interpolation of measured data, the resolution of the IBCAO Ver. 4. 0 Grid may be significantly different to that of the resolution of the underlying measured data. 1 ). (a) Systematic multibeam surveys in 2014 by Swedish icebreaker Oden mapped a trough formed in the ridge crest, Oden Trough, and a critical sill depth influencing water exchange across the ridge  6. In addition, lineations were mapped on the ridge crest, interpreted to be formed by a grounded ice shelf during the penultimate glaciation at about 140 000 years ago  37. None of these features could be seen in IBCAO Ver.
Acknowledgements The compilation of the IBCAO DBM is a part of the  Nippon-Foundation-GEBCO-Seabed 2030  project receiving funding from the  Nippon Foundation of Japan. The authors are deeply indebted to a broad range of agencies and institutions that have funded the collection of bathymetric data in the Arctic (see Online-only Table 2) and have agreed to contribute it to this compilation. Open access funding provided by  Stockholm University.
ΔR weighted mean values and standard deviations were calculated using the deltar function in the Marine Radiocarbon Database from the 14CHRONO Centre  (Reimer and Reimer 2017). Modern seal ΔR values were calculated using the known collection date as the independent age determination. ΔR values for archaeological paired marine-terrestrial samples >200 BP were calculated in deltar, outlined in  Reimer and Reimer (2017)  using the Northern Hemisphere curve. Because the deltar program cannot calculate ΔR values for paired-samples with terrestrial pairs that have ages <200 BP, we followed procedures outlined in  Southon et al. (1995)  to derive ΔR values for these pairs. Terrestrial 14 C ages <200 BP were calibrated in OxCal v4. 3 (Bronk Ramsey 2009) using IntCal13, then terrestrial calibrated age range was converted to modelled 14 C ages using the Marine14 curve  (Reimer et al.
Quality Control of Bone Samples and Radiocarbon Data The atomic C:N ratios and collagen yields for 58% of the study's bone samples were scrutinized to assess the potential for severe protein degradation and for significant amounts of exogenous carbon contamination that would alter the 14 C ages. Atomic C:N ratios are between 3. 1 and 3. 5 with an average of 3. 3 ± 0. 1 falling within the recommended ranges of 2. 9-3. 5 or 3. 1-3. 5 for accepting collagen as preserved enough to yield an accurate 14 C age  (DeNiro 1985; van Klinken 1999). Collagen yields on these samples are between 2. 3% and 31. 0 %yield, with an average of 17. 6 ± 6. 4 %yield, well above acceptable levels >1-to-3. 5 %yield for well-preserved collagen  (Ambrose 1990; van Klinken 1999). Therefore, we consider the collagen quality to be high and exogenous carbon contamination to be minimal in contributing to inaccurate 14 C ages.
Chi-square tests for within groups of terrestrial and marine dates from a given feature were also preformed to define and reduce the influence of outliers on R(t) and ΔR values  (Ascough et al. 2009 ) (Table  S2 ). Five of the 84 (5. 9%) 14 C dates were removed due to internal inconsistencies (outliers) within groups of terrestrial and marine samples within a given feature (Table  1 ). Four bone ages (three caribou and one seal) were removed from the data set, as well as one 14 C date on a piece of structural wood in the tunnel of a house feature at Cape Espenberg that may be driftwood. As a result, the total included 80 paired samples after the statistical outliers were removed from the total data set. Features with multiple 14 C dates on terrestrial and marine samples that were statistically similar were subsequently averaged to create 24 marine-terrestrial paired data sets to use in our calculations of R(t) and ΔR.
ACKNOWLEDGMENTS We thank zooarchaeologists  Carol Gelvin-Reymiller , then of  Northern Land Use Research, Inc. , and  Dr. Holly McKinney  of the  University of Alaska Fairbanks  for aiding in the identification of seal and caribou remains from many of the study sites. Northern Land Use Research Alaska, Inc. funded 14 C ages for the Deering, Kivalina, and Kotzebue sites and modern seal skulls. We thank the  Deering, Kivalina ,  Kotzebue , and  Shishmaref  communities for supporting these archaeological projects and allowing us to sample these collections for the purpose of this study. Eric Carlson , former NLURA archaeologist, supported us in selection of Kotzebue samples and provided notes on their context. National Park Service supported the Maiyumerak Creek excavations and analyses. The  National Park Service  also funded research at Cape Krusenstern through a cooperative agreement ( J8W07070032 ) managed by the  Pacific Northwest Cooperative Ecosystem Study Unit.
Reconstructions of global hydroclimate during the Common Era (CE; the past ∼ 2000 years) are important for providing context for current and future global environmental change. Stable isotope ratios in water are quantitative indicators of hydroclimate on regional to global scales, and these signals are encoded in a wide range of natural geologic archives. Here we present the Iso2k database, a global compilation of previously published datasets from a variety of natural archives that record the stable oxygen (δ 18 O) or hydrogen (δ 2 H) isotopic compositions of environmental waters, which reflect hydroclimate changes over the CE. The Iso2k database contains 759 isotope records from the terrestrial and marine realms, including glacier and ground ice (210); speleothems (68); corals, sclerosponges, and mollusks (143); wood (81); lake sediments and other terrestrial sediments (e.
g. , loess) (158); and marine sediments (99). Individual datasets have temporal resolutions ranging from sub-annual to centennial and include chronological data where available. A fundamental feature of the database is its comprehensive metadata, which will assist both experts and nonexperts in the interpretation of each record and in data synthesis. Key metadata fields have standardized vocabularies to facilitate comparisons across diverse archives and with climate-model-simulated fields. This is the first global-scale collection of water isotope proxy records from multiple types of geological and biological archives. It is suitable for evaluating hydroclimate processes through time and space using large-scale synthesis, model-data intercomparison and (paleo)data assimilation.
, 2016; Thompson et al. , 1986 ). Snow accumulation rates can be strongly affected by air temperature, whereas grain size is generally not. Thus, although comparison of such heterogeneous hydroclimatic proxies is certainly possible, the lack of a common environmental signal to serve as a reconstruction target has been a major hindrance to the global reconstruction of hydroclimatic variables. These challenges have been further exacerbated by archive-and record-specific standards for data formatting, sampling resolution, metadata availability, and public archiving. These limitations may be addressed by creating a metadata-rich, multi-proxy, and multi-archive database of hydrological proxies united through standardized formatting and a common environmental signal: water isotopes.
1 ). Global databases of isotopic measurements of modern precipitation (IAEA/WMO, 2019), rivers  (Halder et al. , 2015) , seawater  (LeGrande and Schmidt, 2006) , and water vapor  (Galewsky et al. , 2016)  have contributed consider-Figure  1. Schematic illustration of the global water cycle and key metadata fields in the Iso2k database. In the Iso2k database, the histories, including phase changes and transport ("Isotope Interpretation"; red text and arrows), of different pools of environmental waters ("Inferred Material"; bold text) can be inferred by interpretation of proxy records from different archives ("Archive"; italic text). Base illustration by Helen Xiu, Washington University. ably to our understanding of the contemporary water cycle on scales from microscales (e. g. , cloud microphysics)  (Kurita et al.
, 2019a; Thompson et al. , 2011). One of the obstacles to synthesizing hydroclimatesensitive paleoclimate records has been a lack of standardized metadata at the proxy system level that systematically encodes the important variables that are necessary for integrating records into a multi-proxy synthesis and interpreting the results. Although the paleoclimate community is in the process of defining and adopting metadata conventions  (Khider et al. , 2019) , the "bare minimum" current standards (e. g. , ISO 19115 for geographic metadata) used by World Data System (WDS) repositories (e. g. , NOAA Paleoclimatology, PANGAEA) are insufficient for characterizing water isotope proxy systems in a way that can be reliably applied to large-scale paleo-hydroclimate syntheses. One key example of this challenge is the temperature dependence of O-and Hisotopic fractionation, which has frequently been exploited to reconstruct past temperature changes in locations where air or water temperature exerts first-order influence on isotope ratios in precipitation and/or seawater  (Kilbourne et al.
Additional metadata challenges have hindered progress in paleo-water isotope synthesis thus far. Most published datasets shared outside WDS repositories follow nonuniform metadata standards or contain minimal metadata. Datasets are often catalogued using different conventions (often at the authors' discretion), stored in varying formats (e. g. , text, CSV, PDF), and uploaded to different public or private (i. e. , behind journal paywalls) repositories. Furthermore, datasets are frequently archived without the raw chronological information that would be required to propagate age uncertainties if desired. These challenges are common to any paleoclimate synthesis effort and are not unique to water isotopes  (Atsawawaranunt et al. , 2018; Emile-Geay and Eshleman, 2013; PAGES 2k Consortium, 2017) , but they exacerbate the challenge of hydroclimate-specific metadata needs.
The PAGES Iso2k database Here we introduce the Past Global Changes (PAGES) Iso2k database, a collection of 759 water isotope proxy records (i. e. , individual time series) from 506 sites (geographic locations) covering all or part of the CE. The database has been assembled by the PAGES Iso2k Project (hereafter "Iso2k"). The Iso2k database contains δ 18 O and δ 2 H-based paleoclimate records from 10 different archives: glacier and ground ice (210 records); speleothems (68 records); corals, sclerosponges, and mollusks (143 records); wood (81 records); terrestrial and lake sediments (158 records); and marine sediments (99 records). Of these, 606 records are considered to be the primary time series for each site (Fig. 2 ) (see Sect. 2. 4 and Table  S1  in the Supplement). To address the complexity of environmental signals preserved in these proxy records, the database contains detailed metadata about each record's isotope systematics and proxy system context, as well as details about the original authors' climatic interpretation, chronological and analytical uncertainties, and other information required for robust data synthesis and interpretation.
Iso2k has developed a uniform framework suitable for all proxy archives in the database. The architecture of the Iso2k database therefore provides a scalable foundation on which future multi-proxy hydroclimatic databases can be built, for example, by incorporating non-isotopic proxy records, such as the grain size and ice accumulation example in Sect. 1. 1. The Iso2k database is the latest in a series of communityled paleoclimate data synthesis efforts endorsed by PAGES  (Atsawawaranunt et al. , 2018; Kaufman et al. , 2020; Mc-Gregor et al. , 2015; McKay and Kaufman, 2014; PAGES 2k Consortium, 2013 , 2017; Tierney et al. , 2015). The main distinguishing feature of the Iso2k database is that it is not organized around one archive type, climate variable, or region; rather, it contains a systematic representation of the suite of environmental signals preserved in the water isotopic composition of diverse paleoclimatic archives, with no a priori assumptions about the underlying climatic interpretation of those signals.
This novel approach yields a database that is flexible enough to evaluate many different environmental parameters and processes during the CE, depending on investigator interest. The Iso2k database also contains even more comprehensive metadata descriptions than  previous PAGES compilations (e. g. , PAGES 2k Consortium, 2017). Database users can therefore filter for and process only the records required for their research question of interest. This data descriptor presents version 1. 0. 0 of the PAGES Iso2k database. We describe the collaborative process of assembling the database (including quality control and valida- tion) and outline the structure and contents of the database (including data selection criteria, metadata, and chronological information). All data are provided in the Linked Paleo Data (LiPD) format  (McKay and Emile-Geay, 2016)  and are machine readable across different platforms and operating systems.
We provide files with sample code to quickly explore the database using various programming languages and platforms (R, MATLAB, Python). The Iso2k database is available for download at https://doi. org/10. 25921/57j8-vs18 (Konecky and McKay, 2020). The database can also be accessed via the NOAA NCEI World Data Service for Paleoclimatology (WDS-NOAA) landing page: https://www. ncdc. noaa. gov/paleo/study/29593 (last access: 30 July 2020). The WDS-NOAA landing page contains links to download the serializations for R, MATLAB, and Python, as well as information on submission of new or revised datasets and other instructions. More information on versioning, submission of new datasets, and other database updates can be found in Sect. 6. 3.
Collaborative model Iso2k is a contribution to Phase 3 of the PAGES 2k Network  (PAGES 2k Network Coordinators, 2017). Calls for participation in Iso2k were widely distributed, ensuring a representative cross section of scientists from various disciplines  (Konecky et al. , 2017 (Konecky et al. , , 2018 (Konecky et al. , , 2015;; Partin et al. , 2015). Iso2k built on the successes and challenges of previous PAGES 2k projects  (Anchukaitis and McKay, 2014; Kaufman, 2014; PAGES 2k Consortium, 2017; PAGES Hydro2k Consortium, 2017)  when deciding on the selection criteria (i. e. , requirements for inclusion of records) and metadata fields necessary to make the database suitable for a wide range of applications. Most work was done remotely via teleconferences, with one in-person meeting at the 2017 PAGES Open Science Meeting in Zaragoza, Spain.
Data aggregation and formatting The database comprises publicly available water isotope proxy records that span all or part of the CE and meet the criteria outlined in Sect. 2. 3. The database was compiled in two main stages. During the first stage, the archive teams obtained records, entered data, and compiled the extensive metadata outlined in Sect. 4. During the second stage, the data and metadata were extensively quality-controlled following the procedure outlined in Sect. 2. 4. We used a variety of sources to identify records for inclusion in the database. We first extracted records that met our selection criteria (described in Sect. 2. 3. 1) from existing data compilations, including the PAGES 2k temperature database (PAGES 2k Consortium, 2017), the Arctic Holocene Transitions database  (Sundqvist et al.
, 2014) , and the SISAL database  (Atsawawaranunt et al. , 2018). Archive teams then searched the literature and online data repositories (WDS-NOAA and PANGAEA) for additional suitable datasets. For records that had been published but that had not previously been made available in an online public repository (referred to as "dark data"), datasets were digitized from publication tables, appendices, and supplementary materials. Datasets that were not available in their original publications were requested from the authors by email. If two or more email requests went unanswered, the dataset was deemed not publicly available and therefore did not meet that criterion for inclusion in this database. Of the 606 primary time series in the database, more than 20 % (128 records) are dark datasets that were added by Iso2k members and are now available in a public, online, machine-readable format for the first time.
The vast majority of those datasets were from wood or from lake and terrestrial sediments (58 and 52, respectively), with an additional 14 from glacier and ground ice, 2 from marine sediments, and 2 from corals. In addition to isotopic datasets, raw age control data (e. g. , 14 C ages) were obtained for records where age-depth modeling is required (i. e. , non-annually resolved records). Many isotopic datasets that were available through data repositories did not contain raw age control data, in which case we followed the dark data procedure described previously to obtain appropriate chronological data from the authors. For dark age control data, authors were emailed with a request for the data and a spreadsheet template in which chronological information could be added. Age control data from authors who did not respond to these requests could not be added to the database.
Again, the majority of "dark" age control data added to the Iso2k database was from the lake sediments archive (over 40 age control datasets are now publicly available for the first time). Metadata (Sect. 4) were obtained from the data source, extracted from the original publication, or requested from the original data generators (again following the dark data procedure above). We note that even for datasets that were previously publicly available, the Iso2k database has expanded on these data by adding chronological data and compiling an extended suite of metadata not previously available in a consolidated format.
Record resolution and duration The duration and temporal resolution of records included in the Iso2k database varies by archive type. For ∼ annually or ∼ sub-annually banded archives (corals, shells, sclerosponges, tree wood, varved lake and marine sediments, and glacier ice), the minimum record duration for inclusion in the database is 30 years. For all other archives (speleothems, non-varved lake and marine sediments), records must have a minimum duration of 200 years and contain at least five data points during the CE.
Chronological constraints The PAGES 2k temperature database (PAGES 2k Consortium, 2017) was used as a guide for minimum chronological control criteria. Records from annually banded archives must be either cross-dated or layer-counted; records from non-annually banded archives must have at least one age control point near both the oldest and youngest portions of the record, with one additional age control point somewhere near the middle required for records longer than 1000 years.
Ancillary data In some cases, paired geochemical measurements are also included in the Iso2k database to complement interpretation of the isotopic data, such as paired trace elemental measurements (e. g. , Sr/Ca or Mg/Ca) that accompany some carbonate δ 18 O records from corals, sclerosponges, and planktonic Earth Syst. Sci. Data, 12, 2261 Data, 12, -2288 Data, 12, , 2020  https://doi. org/10. 5194/essd-12-2261-2020 foraminifera, or δ 13 C data that accompany some carbonate records. Derived isotopic data for deuterium excess (dexcess) are also included for glacier and ground ice, where paired measurements of δ 18 O or δ 2 H allowed the original authors to calculate this additional hydroclimatic indicator. Similarly, derived values for the δ 18 O of seawater are available for coral and marine sediment records in cases where an independent temperature reconstruction was available for the same archive (e.
g. , Sr/Ca for corals and Mg/Ca for planktonic foraminifera). Where the paired carbonate δ 18 O and Sr/Ca or Mg/Ca records can be used to infer the δ 18 O of seawater  (Cahyarini et al. , 2008; Elderfield and Ganssen, 2000; Gagan et al. , 1998) , both time series (δ 18 O measured directly on carbonate and δ 18 O seawater calculated from paired records) and ancillary, non-isotopic geochemical records are included in the database (Sect. 4).