dataesr/scientific-paragraphs-categorization huggingface dataset:
Flood risk and insurance Lastly, we incorporate measures of exposure to flood risk and insurance take-up. For exposure to flood risk, we use data from the First Street Foundation (FS) Flood Model  (Bates et al. , 2021; First Street Foundation, 2020). The FS model is a high-resolution model of the risk of flooding in the contiguous United States due to rainfall (pluvial), riverine (fluvial), and coastal surge flooding  (Bates et al. , 2021; First Street Foundation, 2020). It provides in particular an estimate of the percentage of properties at risk in 2020 at the ZIP code level. We denote this variable as (FS2020) and use it as a benchmark measure of exposure to flood risk, corresponding to current climate conditions. In addition to the 2020 estimates, the FS dataset includes projections of the impact of climate change on the percentage of properties exposed to flood risk.
Model selection Before estimating the models, we split the observations in a training sample and a control sample within a K-fold cross-validation framework (with k set to 5) using the 𝑐𝑟𝑒𝑎𝑡𝑒𝑓 𝑜𝑙𝑑𝑠() function available in the R package 𝑐𝑎𝑟𝑒𝑡  (Kuhn et al. , 2020). We construct the K-fold by sampling from the list of 69,046 loans. Afterward, we merge the training and control sample IDs with loan-month observations to estimate the model and assess the predictive accuracy. For simplicity, we describe the results of one of the five training samples defined within the crossvalidation framework. As we found similar estimates on the different sets, we can infer that our empirical results are robust. We estimate the additive Cox proportional hazard model with timevarying covariates using the 𝑏𝑎𝑚() function implemented in the R package mgcv  (Wood, 2021).
Acknowledgments We would like to thank the Editor and the reviewers for their constructive suggestions which helped to improve the paper. The paper was presented at several seminars and conferences, including the 20th International Conference on Credit Risk Evaluation -Compound Risk: Climate, Disaster, Finance, Pandemic, the 38th Annual Meeting and Conference of the American  Real Estate Society , the DXDE 2021: Digital Transformation and Digital Economics, the  U. S. Federal Housing Finance Agency seminar , and the  11th Annual Research Workshop -Technological Innovation, Climate Finance and Banking Regulation  organized by  European Banking Authority. We thank the participants at these events for their helpful comments and suggestions. Antoine Mandel  acknowledges funding from the  European Union 's  Horizon Europe research and innovation program  under grant agreement  DECIPHER  nb  101056898.
https://github. com/geanders/stormwindmodel winds greater than 95 knots (black areas) at Hurricane Michael's landfall in Florida. After estimating wind speed for each location, we have used the Saffir-Simpson hurricane wind scale to classify the tropical cyclone category. Specifically, we have defined a categorical variable as follows: no events (in the absence of tropical cyclones or wind speeds lower than 34 knots), tropical storm (34-63 knots), hurricane category 1 (64-82 knots), hurricane category 2 (83-95 knots), hurricane category 3+ (greater than 95 knots). In the 2010-2019 period, based on the National Hurricane Center classification, Florida was exposed to eight tropical storms and six hurricanes. In particular, Fig. 3displays how hurricanes of category 2+ have been rare events. However, they are important events for risk managers because they can potentially cause material damages when they occur (e.
g. , Pielke et al. (2008) ). Looking at precipitations, several indices of intensity of rainfall are proposed in the literature (e. g. Zhang et al. , 2011). We consider using as a measure of rainfall intensity the monthly maximum accumulated consecutive 5-day precipitation (Rx5day) in millimeters (mm). The Rx5day is computed as the 𝑚𝑎𝑥(𝑃 𝑅𝐸𝐶 𝑡𝑚𝑦 ), where 𝑃 𝑅𝐸𝐶 𝑡𝑚𝑦 is the precipitation amount > 1 mm for the 5-day interval ending 𝑡, in the month 𝑚 of the year 𝑦. We compute the Rx5day using the information on total precipitations recorded in the ERA5 database of Copernicus (Hersbach et al. , 2018). The data on precipitations (accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface) are in a regular latitude-longitude grid of 0. 25 • × 0. 25 • (≈ 30 km) with an hourly temporal resolution.
5000 cal. BC. A lagoonal landscape developed from the Neolithic until Greek colonists settled in the area c. 654 BC. The results presented here suggest that the relocation of the city in the 4th century BC was not caused by the silting up of the bay but was due to historical events. The coastal progradation only became significant after 300 cal. BC and accelerated in the following centuries. Based on the data acquired, it is hypothesized that this was due to anthropogenic forcing of the sedimentary systems both at local and regional levels, caused by the development of the productive activities of the colony. The evidence presented here demonstrates that while Abdera retained good access to the sea, its decline in the 4th c. AD was certainly due to the gradual shift of the economic axis inland.
Archaeological and geomorphological background Data concerning human settlements and societies before the Iron Age in the region (see Table  1  for the chronological framework in NE Greece) are rather scarce. One of the few significant prehistoric sites recorded in this coastal area is a partly underwater shell mound adjacent to the Lafrouda lagoon, a few kms NE of the study area, and dated c. 5500-5200 cal. BC. The few documented Iron Age Thracian sites are mostly located inland in the foothills of the Rhodope mountains  (Kallintzi, 2011; Kallintzi et al. , 2021). The main historical event in the area was foundation of the Greek colony of Abdera around 654 BC by Ionian colonists from Klazomenai. It was re-settled later by Teians in 545 BC  (Moustaka et al. , 2004; Kallintzi, 2011)  and quickly became a wealthy and prosperous city.
Remote Sensing, cartographic data and geomorphological mapping Historical aerial imagery was obtained from different photographic flights provided by the Hellenic Military Geographical Service  (1938, 1945, 1960, 1978, 1989, 2002) , and more recently imagery was gathered from Google Earth, Microsoft Zoom Earth, and Esri World Imagery. Satellite imagery from Sentinel 2 (2015 onwards) was processed to obtain the Seasonal Multi-Temporal Vegetation Indices (SMTVI, see Fig. 5 ), which have provided useful composite imagery for the detection of geomorphological features  (Orengo & Petrie, 2017). Several Digital Elevation Models (DEMs) with different resolutions and coverage ranging from macroscale to detail scale were combined to cover all the study area. ALOS30 and EUDEM25, two large-scale DEMs with global coverage and a similar resolution (30 and 25 m/pixel respectively), were used as background topographic data.
Radiocarbon dating and RSL modelling A total of 34 samples were sent to various laboratories for AMS radiocarbon dating (Beta Analytics, DirectAMS, Paris-Saclay, and the Arizona Climate & Ecosystems Isotope Lab, see Table  3 ). Dated materials include marine shells in anatomical connection and living at (or very close to) the water-sediment interface, remains of Posidonia oceanica sheaths, terrestrial plant and wood fragments or smaller debris, and charcoal. Raw dates were calibrated with the Calib v. 810 software using the INTCAL20 calibration curve for terrestrial samples and the MARINE20 curve for marine samples  (Stuiver & Reimer, 1993; Heaton et al. , 2020; Reimer et al. , 2020). For the latter we used a DeltaR of -8 ± 40 yr. (Siani et al. , 2000). The depths of the samples in Table  3  are raw depths measured directly in the cores, although they were later corrected for decompaction and construction of the composite cores when necessary.
The radiocarbon dataset was also used to reconstruct changes in Relative Sea Level (RSL) in the area, adapting the methodology proposed by Vacchi  (Vacchi et al. , 2016). However, a more conservative approach was adopted here through the knowledge that all the radiocarbon dates in our sample can only be interpreted as marine lower limiting points, and not directly indicative of RSL. The corrected depths of 25 selected dates (the 9 aged dates -see Table  3 -were not used for RSL reconstruction) were converted into altitude below (current) mean sea level and plotted together on a graph with error bars (age and depth). A sub dataset of 14 samples (10 shells, 4 plant samples, see Table  4 ) was selected to build a curve of estimated Minimal Relative Mean Sea Level (MRMSL). The criteria for selection were the types of sedimentary facies the samples were recovered from, the nature of the samples, ecology of the shells -intertidal to shallow subtidal-  (Vacchi et al.
, 2016) , and their consistency with the other limiting points. The rest of the dates (11) were considered subtidal in a broad sense. We added 30 cm to the altitudes of the samples, considering that all were found in aquatic/marine facies -i. e. , below some centimetres of water even during low tides-and that the mean tide amplitude in the area is 26 cm  (Pavlopoulos et al. , 2012). The vertical uncertainty is a sum of the Z precision of the DGPS measurements, the estimated error in depth measurements when coring and posterior corrections for compaction, and the maximum burrowing depth of Cerastoderma sp. and Loripes sp. shells, that is ~ 5-10 cm (see  van der Geest et al. , 2011; Anacleto et al. , 2016). Two dates from a previous sea-level study in the area  (Pavlopoulos et al. , 2012)  were also recalibrated using the modern standards of this study and incorporated into the final dataset for MRMSL estimation.
These dates, a charcoal obtained from a Neolithic shell mound layer and a piece of driftwood associated with marine transgression, were considered to be slightly supratidal and intertidal limiting points respectively (see  Ammerman et al. , 2008 for details). A polynomic curve was fitted as close as possible to the whole dataset, and the Mediterranean Sea level of 1950 was also used as an intersection point at 0 cal. BP  (Calafat & Gomis, 2009).
650 cal. BC as based on the archaeological data (Klazomenian ship sheds, Fig. 3 ). By then, the Valta Zambaki lagoon had silted up and was a marsh with dry margins (Fig. 7 ). A second washover deposit (AVZ4) suggests that in the centuries that followed intense storm activity may have temporarily increased the connection the marsh had with the sea and its water depth. Radiocarbon dates in the seabed facies at the base of AVH1 and AVH2 suggest that by the 4th c. BC the water depth was relatively shallow in front of beach-barrier 1 (≥1. 75 m, considering an RSL of -60 cm for this period -  Pavlopoulos et al. , 2012). Coastal progradation was certainly only incipient, if at all existent, at this time, and the massive beach-barriers 2 & 3 grew later in Hellenistic and Roman times (3rd c. BC to mid-2nd c.
Middle-to Late Holocene Relative Sea-Level changes in the Cape Bouloustra area Fig. 10  shows the Minimum Relative Mean Sea Level (MRMSL) curve from 7250 cal. BP reconstructed using a subset of radiocarbon dates obtained in this study as marine limiting points (Table  4 ). Two recalibrated dates from a Neolithic shell mound located 5 km NE of Abdera close to the Lafrouda lagoon (see  Ammerman et al. , 2008; Efstratiou, 2016)  have also been added. The polynomial MRMSL curve fits the whole dataset well (R 2 > 0,95). Considering that our marine limiting points are mostly intertidal to slightly subtidal, we argue that our reconstruction is accurate and that the exact RMSL was very close -likely only a few centimetres-above the MRMSL curve. This is also supported by the consistency our dataset shows with the two previous dates from the Lafrouda Neolithic shell mound  (Ammerman et al.
4500 cal. BC the marine transgression was much slower and could partly have been compensated by sedimentary inputs from terrestrial areas. More stable coastal dynamics are also suggested by the formation of the first beach-barriers and lagoons in the area from c. 5000 cal. BC (Figs. 7 8 9 ). The dataset does not support a mid-Holocene high-stand in the area, although this hypothesis has already been widely discussed and contested for the Aegean (e. g. Brückner et al. , 2010; Vacchi et al. , 2014). By contrast, the MRMSL curve shows a relative slowdown in the rise of levels between 5500 and 3500 cal. BP, and especially in the 5th millennium cal. BP, with a MRMSL of -1. 5 m with respect to the current level. Although a distortion due to the nature of the dataset and the process of construction of the curve cannot be totally discarded, this slowdown might instead represent a period of slight tectonic uplift of the Abdera horst, as other authors have already suggested  (Pavlopoulos et al.
, 2012). It is noteworthy that this phase seems to correspond to a short emersion phase with incipient pedogenesis in the Valta Zambaki marsh (see Figs. 7  and 8 ) some centuries before 1450 cal. BC, which is indicative of a sedimentary accumulation rate exceeding the RSL rise in the lagoon. The impact of RSL variations documented between the second half of the Late Neolithic and the Late Bronze Age on local human populations is difficult to assess as archaeological data are very scarce. However, increased coastal stability (only a 1 m RSL rise in three millennia, between -2 and -1m) might have been an asset for settlement in the area. Our dataset suggests that when the Klazomenian colony was founded in c. 650 cal. BC (2600 cal. BP) the RSL was c. 70 cm lower than the present level (see Fig.
Conclusions Based on the radiocarbon data from the cores, the first detailed and accurate Holocene sea-level curve for this sector of the Northern Aegean has been built and presented in this article. This curve is consistent with global eustatic models, thus confirming that the Abdera horst was subject to few tectonic movements during the Holocene. The palaeogeographic evolution of the area around Abdera from the Mid-Holocene onwards was reconstructed here, with the main processes and phases of landscape change and their potential drivers also identified. Before 5000 cal. BC, the area was terrestrial due to a much lower sea-level. The first evidence for the drowned Early and Middle Holocene landscapes of this coastal region that was likely occupied with a certain density by Late Neolithic societies was found.
Acknowledgements This research has been funded by the  Spanish Ministry of Science, Innovation and Universities  within the project  TransLands  ( PGC2018-093734-B-I00 ). AM is a  Juan de la Cierva -Incorporación Fellow  of the  Spanish Ministry of Science, Innovation, and Universities  ( IJC2020-045609-I ); AGM is a  Beatriu de Pinós Fellow of  the  Catalan Autonomous Government  ( 2018 BP 00208 ); MG is a  Marie Skłodowska-Curie Fellow leading  the project  TransMed  ( H2020-MSCA-IF-2018-8396 ). The authors also want to acknowledge the support of the  Ephorate of Xanthi , the  Archaeological Museum of Abdera , and the  Greek Ministry of Culture  through the  APAX programme. We are also grateful to a number of people who provided support for this article:  Jean-François Berger ,  Oldrich Navratil ,  Olivier Voldoire ,  Rena Veropoulidou ,  Maxime Burst ,  Santiago Riera ,  Raphaël Paris ,  Konstantina Venieri ,  Alexandra Livarda ,  Josep María Palet , and  Laura Benedito.
The Bahrain_Tylos individuals are slightly differentiated. Compared with the older individual AS_EMT, samples MH1_LT and MH2_LT are shifted towards eastern populations from Armenia ChL-IA composed mainly of CHG-and Anatolian-related ancestry and variable amounts of steppe ancestry, with MH2_LT being further separated from the Bahrain group towards the direction of CHG and ancient groups from Iran and Pakistan. Sample MH3_LT is closer to ancient Levantine groups than the other three individuals from Bahrain. To further investigate the ancestry composition of the Tylos individuals, we performed a temporally aware model-based clustering analysis on an expanded dataset using DyStruct (Figure  1B ). At k=9, Anatolian_N, Natufians, WHG (Western Hunter-Gatherers), and Iran_N/CHG define independent ancestral components which contribute to the majority of ancient and present-day West Eurasians (Figure  1B ; Figure  S6 ).
Tylos-Period Bahrainis are genetically closer to present-day Levantine populations than to present-day Arabians Regarding affinities with present-day populations, the temporally aware model-based clustering analysis (Figure  1B ) suggests that Tylos period Bahrain samples are more similar to present-day Levantine groups than to present-day Arabians or South Asians, who show higher and lower amounts of Natufian ancestry, respectively. To investigate this in more detail, we performed a haplotype-based ChromoPainter and FineSTRUCTURE analysis with a dataset including Tylos-period Bahrainis, ancient samples from the Levant  13, 37  and Iran 10 with available whole genome shotgun sequence data, as well as present-day individuals from the Human Origins dataset 1138 , and from Arabia and the Levant 20 (Figure  4 ).
Three Bahrain Tylos samples (AS_EMT, MH1 and MH2_LT) were included in a cluster composed of Syrians, Iraqis and two Jewish individuals from Iran and Georgia (Figure  4A ), whereas sample MH3_LT clustered with 22 ancient individuals from Lebanon ranging from the Bronze Age to the Roman Period. In a PCA of the haplotype sharing matrix (Figure  4B ), we observe that MH3_LT is closer to ancient Lebanese and Sardinians, corroborating our previous inferences of increased ancient Levantine and Anatolian Neolithic ancestry in this sample. The remaining three Bahrain Tylos individuals are positioned closer to present-day groups from the Levant, Iraq and the Caucasus, including several Jewish populations from these regions, and between ancient Lebanese and an Iranian IA individual. In order to gain further insights into the relationship of Tylos to present-day populations from the Arabian Peninsula and the Levant, we tested if the Bahraini samples form a clade with any modern population in our dataset using a set of reference populations (as outgroups) that can differentiate the different ancestries in the Near East.
Diverse Uniparental Lineages link Ancient Bahrainis to Middle Eastern populations We used pathPhynder  40  to examine the Y-chromosome lineages of two male samples from the Late Tylos-period Bahrain in a context of present-day and ancient samples (Figure  S8 , Table  S11 ). Individual MH3_LT carried the H2 haplogroup which is associated with the spread of Near Eastern and Anatolian farmers into Europe  41. MH3_LT was placed in the same clade as a PPNB Jordanian and two Anatolian samples (Alalakh_MLBA and Ilipinar_ChL), which is consistent with the genetic affinities of this individual (Figure  S8A ). Sample MH1_LT, the only other male sample in our dataset, presented the J2a2a1al ineage, which in a phylogeny with 2,014 individuals is carried by a present-day Brahmin and an Uighur individual.
9). When estimating a phylogeny with the imputed X-chromosome haplotypes containing the mutation of interest, we observe the inclusion of three Tylos-period Bahrainis in a clade with additional samples carrying the derived allele, including present-day Emiratis, Omanis and Yemenis, as well as the Iranian Neolithic sample AH1 (Figure  6A ). In present-day populations, we observe relatively high frequencies of this variant in Makrani (0. 19), Brahui (0. 14) and Pathan (0. 08) population samples, all of which bear high levels of Iranian Neolithic-related ancestry. In Europe frequencies are substantially lower, with a single Sardinian sample carrying the derived allele in the HGDP dataset (0. 03), and three out of 53,000 European individuals in the gnomAD database  58. In the Middle East, it can be found in Palestinians (0.
06), but not in Druze, Bedouins, Jordanians or Iraqis  20. In Arabian populations, the derived allele reaches its highest frequencies in EmiratiC (0. 38), a subgroup of the Emirati who carry substantial Iranian/South Asian-related ancestry (Figure  1B ), and 6% in the rest of the Emirati population. It has also been found in the present-day populations of Yemen (0. 04), and Qatar (0. 03)  32  , but not in Saudis  20. In the Levant and Eastern Arabia, the Mediterranean mutation is responsible for the majority of G6PD-deficient cases, reaching very high frequencies in Bahrainis (0. 91)  59  , Northern Iraqi (0. 88), Kuwaitis (0. 74) and Jordanians (0. 54)  60. In order to search for signatures of selection associated with the G6PD Mediterranean, we performed an extended haplotype homozygosity analysis (EHH) on the haplotypes surrounding this SNP in a dataset of Arabian and Levantine groups.
Sex determination and relatedness analysis We determined the sex of the four ancient samples from Bahrain using a previously published method  79  (Table  1 ). We performed a kinship analysis on the four ancient samples from Bahrain using READ (https://bitbucket. org/tguenther/read/)  80  with default parameters on approximately 1,240k SNPs of the Allen Ancient DNA Resource, genotyped as described below, which did not reveal any close kinship relationships between them.
Principal component analysis and model-based clustering We ran Principal Components Analysis (PCA) using smartpca v18140 from the EIGENSOFT package with parameters numoutlieriter: 0, lsqproject: YES, autoshrink: YES, projecting ancient samples on the principal components estimated with present-day Eurasian populations. We also ran DyStruct (https://github. com/tyjo/dystruct) 116 from K=7 to K=12 in a dataset of 2,073 samples and 85,043 transversions with default parameters across eleven time points binned around the following times (generations ago): 450, 350, 250, 180, 150, 120, 90, 70, 50, 25, and present-day.
F-statistics, qpWave, qpAdm and qpGraph We estimated f3-and f4-statistics and qpAdm using the AdmixTools 2 R package 117. For modelling the ancestry of Bahrain Tylos samples with qpAdm using ancient populations as sources, we used the following right populations: Mbuti. DG, CHG, EHG3, ISR_Natufian_EpiP, MAR_Taforalt_EpiP, RUS_AfontovaGora3, SRB_Iron_Gates_HG, TUR_Pınarbaşı_EpiP and WHG4. For qpWave tests using present-day populations, we used qpWave v1520 from the AdmixTools v7. 0. 2 package (https://github. com/DReichLab/AdmixTools)  31  with option allsnps:YES to test if ancient Bahrain formed a clade with any other ancient or modern populations. We used qpAdm v1520 to estimate ancestry proportions in present-day populations, using the following reference population samples: Mbuti, Ust'-Ishim, Kostenki14, MA1, China_Tianyuan, WHG, WSHG, Natufian, Levant_N, Morocco_Iberomaurusian, Anatolia_N, Iran_N, CHG, EHG, and Steppe_Eneolithic.
Chromopainter analysis We ran the ChromoPainter/finestructure v4. 1. 0 inference pipeline 118 with default settings outputting a co-ancestry matrix with values depicting haplotype segments shared between individuals. We ran the pipeline on a merged dataset composed of the 41 imputed ancient samples and 168 Modern samples from the Middle East, Europe and South Asia  11, 20. We used 448K SNPs which have a minor allele frequency >5% in the reference panel and excluded sites with missingness more than 5%, and jointly phased the merged dataset using the 1000G high coverage reference panel 119 using Beagle v5. 2 120.