dataesr/scientific-paragraphs-categorization huggingface dataset:
For example, heterozygosity excess of the FM09 and FM11 sample groups dropped from 0. 07 to -0. 015, and F IS increased from -0. 255 to 0. 065. Finally, there was strong agreement between relatedness analyses on the (minimal) presence of kin among specimens. COANCESTRY, RelateAdmix and KING all identified the same, lone pair of individuals showing a relatedness coefficient within the range of simulated half sibs in the entire dataset, along with one or two cousin-level pairs. COANCESTRY and RelatedAdmix also reported several thousand dyads with relatedness coefficients lower than the threshold for cousin pairs, but more than would be expected from unrelated individuals (specifically, 8399 dyads using COANCESTRY and 5727 using RelatedAdmix), while KING identified 86 such dyads. Direct comparisons of these results with the results of  Anderson et al.
Indeed, an excess of sibship was found among 5-11 day old larvae of the related Atlantic bluefin tuna samples by  McDowell et al. (2022). Further representative sampling of larvae and juveniles has long been identified as a research need to improve our understanding of tropical tuna population structure, and plans are afoot to obtain larval samples during upcoming collaborative research cruises. While the steps taken in this work to address cross-contaminations have improved the reliability of the corrected dataset, caution should still be exerted during interpretation of the results. The present study implemented enhanced protocols for sample handling and postsequencing checks, resulting in a significant reduction in sample cross-contamination compared with the  Anderson et al. (2019)  dataset.
g. half-first cousins), a degree of similarity more likely to arise naturally and not through contamination effects. The sole statistically significant pairwise FST value could potentially be    2019 ) are available to identify and filter out compromised loci and individuals from next generation sequencing datasets. These methods require sequencing read processing and SNP calling to be done in house. This was not possible in the present study, which sought to remain compatible with the  Anderson et al. (2019)  dataset by utilising DArT PL services to process raw data through SNP calling and to undertake preliminary quality filtering. Regardless, given the strength of evidence against the presence of strong population structure as shown by our new data, we believe that additional filtering steps are unlikely to alter this overall conclusion.
Some discussion is warranted on the likely source of contamination events in the original dataset presented by  Anderson et al. (2019). Handling of samples always introduces the risk of contamination, even by experienced field and laboratory staff. Even professional sequencing labs can be a potential source of contamination  (Ballenghien et al. , 2017). The use of ethanol and flame treatment during the sample preparation phase was also possibly a weak point, since ethanol does not denature DNA and heat is likewise not recognized as a highly effective treatment  (Wang et al. , 2014). However, if this was the sole source of contamination, then samples would likely have been compromised at the same rate across groups. Instead, the concentration of contamination among Micronesian samples from FM09 and FM11 suggests that local deviations in onboard or onshore sampling protocols may have increased the rate and intensity of contamination in those groups.
Conclusion We revisited data published in 2019 that indicated population genetic structure among yellowfin tuna in the WCPO. By resequencing a suspect part of the dataset, we found that the results were not reproducible. Instead, our new results indicate a lack of evidence for genetic population substructuring across the study area spanning Papua New Guinea to the Gilbert Islands, Kiribati, over six years of sample collection. The most likely explanation is that the original dataset was compromised by cross-contamination, which was reduced through the amended laboratory handling and data filtering protocols used in the present study. It is possible that population structure exists but was not observed in this study, in particular local adaptation driven by loci under selection not captured by our genotyping assay.
Structure may also be revealed when sampling alternative life stages as shown in other tunas. Finally, population structure can occur at time scales that are important to management processes but not measurable by genetic processes. We therefore encourage continued exploration of yellowfin tuna population structure using a diverse array of methods. We also highlight the need for the refinement and rollout of sampling standard operating procedures for fisheries genetics and genomics applications that reduce the potential for sample cross-contamination from the point of collection to sequencing. Funding was provided by the Western and Central Pacific Fisheries Commission (Project 35b) and the European Union "Pacific-European-Union-Marine-Partnership" Programme (agreement FED/2018/397-941). This publication was produced with the financial support of the European Union and Sweden.
We report progress on the ongoing recalibration of the Wolf sunspot number (S N ) and groupsunspot number (G N ) following the release of version 2. 0 of S N in 2015. This report constitutes both an update of the efforts reported in the 2016 Topical Issue of Solar Physics and a summary of work by the International Space Science Institute (ISSI) International Team formed in 2017 to develop optimal S N and G N reconstruction methods while continuing to expand the historical sunspot-number database. Significant progress has been made on the database side while more work is needed to bring the various proposed S N and (primarily) G N reconstruction methods closer to maturity, after which the new reconstructions (or combinations thereof) can be compared with (a) "benchmark" expectations for any normalization scheme (e.
This simpler index does not include the count of individual spots, which characterizes the varying size of the sunspot groups but is often missing in early observations. A key advantage of the G N series was that  Hoyt and Schatten (1998a,b)  were able to reconstruct it back to the first telescopic observations of sunspots by Galileo and others ca. 1610 vs. the initial year of 1700 for Wolf's S N series. The new G N thus encompassed the period of extremely weak sunspot activity from 1645 -1715 known as the Maunder Minimum  (Eddy, 1976; Spörer, 1887 Spörer, , 1889;; Maunder, 1894 Maunder, , 1922)). Until recently, another crucial advantage of G N was the availability of all the raw source data in the form of an open digital database, while the S N source data, forming a much larger collection (more than ∼800 000 observations), were available in digital format only since 1981 (Brussels period).
0) series over  1920 -1974. They agree closely over the twentieth century, but diverge significantly for earlier centuries. The latest moderate cycle (number 24) matches the amplitude of the solar cycles at the turn between the nineteenth and twentieth centuries, which are clearly higher than the Dalton minimum in the early nineteenth century and the Maunder minimum of the seventeenth century. The latter is covered only by the G N reconstructions. Chatzistergos et al. (2017; CEA17). Modifications to UEA16 were published by  Willamo, Usoskin, and Kovaltsov (2017; WEA17)  and WEA17 was subsequently modified by basing it on the new  Vaquero et al. (2016; V16 herein; 16  for the year of release) database 2  rather than the original  Hoyt and Schatten (1998a,b)  database  (Usoskin et al. , 2021; UEA21).
Data Recovery: The Sunspot-Number Database Data recovery is a never-ending task, and future revisions of sunspot series will occur intermittently as part of a continuous upgrading process. The last few years have witnessed significant advances in recovery and digitization of data underlying the S N time series, particularly in the context of the ISSI Team collaboration over 2019 -2021. The focus in this section is on sunspot observations that were either made at Zürich and later at Locarno and Brussels for the creation of S N , or collected and archived from external observatories by the Directors of the Zürich Observatory, and since 1981 by the World Data Center for Sunspot Index and Long-term Solar Observations (WDC-SILSO) in Brussels, for this purpose. The Zürich sunspot number produced by Wolf and his successors from 1700 -1980 is based on three types of data: (1) the raw counts from the Zürich observers (the director and the assistants) from 1848 -1980, (2) corresponding counts sent to the Observatory of Zürich by external auxiliary observers, and (3) historical observations for years before 1849 collected mainly by Wolf but also by Wolfer, his successor.
Much of this material was published over the years in the bulletins of the Zürich Observatory, the Mittheilungen der Eidgenössischen Sternwarte Zürich (hereafter, the Mittheilungen). This is a fundamental resource for any future recomputation of S N. Until recently, this large collection of printed data was completely inaccessible in digital form. During 2018 -2019, a full encoding of the Mittheilungen data tables, from the printed originals, was undertaken at WDC-SILSO in Brussels, constituting the initial segment of the sunspot-number database. This includes all data published between 1849 and 1944 (black curve in Figure  3 ) when Max Waldmeier, the last Director of the Zürich Observatory decided to cease publishing raw data. This database now contains 205 000 individual daily sunspot counts  (Clette et al.
, 2021) : it currently includes data from the Zürich and auxiliary observers between 1849 and 1944, and all long data series in the early historical part, from 1749 to 1849, that were found and collected by Wolf in his epoch. (NB: Isolated observations, randomly scattered over time, are less exploitable and will be added later. ) In addition to daily counts of spots and groups, the database includes metadata -in particular, changes of observers or instruments. Although the published data were globally comprehensive, some parts are missing. The Mittheilungen provide the full set of observations from the Zürich team itself only from 1871 onwards, when Wolf started to publish separate tables for himself and his assistants as well as data received from external observers  (Friedli, 2016). Before 1871, Wolf published only a single yearly table, with all his own observations, and data from external observers or assistants were only included to fill the remaining random missing days.
Unfortunately, following the closing of the Observatory of Zürich in 1980, when the curatorship of the sunspot number was transferred to ROB, those unpublished archives went missing. Figure  3  (brown and blue curves) shows the resulting major ∼60-year shortfall  (1919 -1979)  in the preserved raw data. The absence of a large portion of the 1919 -1979 sunspot data constituted a critical missing link between the early Zürich epoch and the modern international sunspot number produced in Brussels since 1981, for which all data are preserved in a digital database. 3 In particular, this period spans one of the main scale discontinuities identified in the Zürich series, the "Waldmeier jump" in 1947  (Clette et al. , 2014; Lockwood, Owens, and Barnard, 2014a; Clette and Lefèvre, 2016; Svalgaard, Cagnotti, and Cortesi, 2017).
8) and are accessible online on the Swiss e-manuscripta portal (www. e-manuscripta. ch). This recovery already delivered key explanations regarding the main discontinuity formerly found in 1947 in the S N series  (Clette et al. , 2021 ; see below), but the time-consuming digitization of the huge set of observations (more than 300 000 daily numbers) to expand the S N database will require more resources and time. Simultaneously, efforts are continuing to 3 1980 was a disturbed closing year at the Zürich Observatory. The standard yearly tables of source data were not produced by the Zürich staff, and the resulting sunspot numbers were published as crude typewritten pages instead of the normal printed edition of the Mittheilungen. However, the original reports sent to Zürich by all auxiliary stations were recovered and were transferred in 2007 to the World Data Center SILSO in Brussels.
This approach thus rested entirely on the personal life-long stability of individual reference observers, and on the assumed equivalence "by construction" of successive observers observing from the same place with mostly the same instrument. Any correction thus implies the use of alternate observers. Unfortunately, as described in the previous section, until recently, the Zürich source data were not available in digital form and part of the archives were even missing, which prevented any reconstruction from a wide base of source data from multiple alternate observers. Reconstructing a sunspot database for the entire Zürich period before 1980 will thus be a key step for any future upgrade of the S N series. This focused the efforts over the last few years, as described in the previous section and also in Section 2.
Following the creation of the S N database and the recent recovery of all source data for the period  1945 -1980 , Clette et al. (2021) )  conducted a full survey of contributing stations since Wolf started recruiting assistants and auxiliary observers, up to the Waldmeier period that concludes the Zürich era of the S N , with its extended worldwide network of auxiliary stations (cf. Section 2. 1. 1). The resulting timelines revealed two unique disruptions in the history of the Zürich sunspot number that occurred almost simultaneously, immediately after the end of WW II. Due to the war, the former set of contributing stations was replaced by an entirely new and larger international network of auxiliary stations in the years following 1945. At the same time, in Zürich, Brunner and his primary long-term assistant continued to observe until the end of 1946, and were then replaced by Waldmeier and by new assistants, among whom the first ones only stayed at the Observatory for a short time (Figure  6 ).
Another obvious improvement would consist in replacing the single preselected pilot observer by a set of reference stations, selected on the base of systematic statistical quality criteria  (Clette and Lefèvre, 2016). The elements of such a method are now developed and trained on actual data from the SILSO network. This new state-of-the-art approach, presented by ISSI team members  (Mathieu et al. , 2019 (Mathieu et al. , , 2023)) , uses advanced statistical techniques to derive a nonparametric measure of the short-and long-term stability of each individual observer or observatory team, and it also introduces a proper nonnormal distribution of uncertainties, in particular in the special case when the S N is close to zero, with the constraint of nonnegativity. In addition to creating a new time series, such tools can form the basis for a permanent quality-monitoring process, applicable both to the past reconstruction and to the current and future production of the S N at the WDC-SILSO.
However, gathering enough base data remains the essential prerequisite for any progress. This will thus require recovering more historical and revising the existing data series, which were often inherited indirectly through past data searches, sometimes a long time ago. For the twentieth century, except for the remaining lost Zürich archives between 1919 and 1944, we now have reasonable data coverage. Still, even for this more recent period, new data series that were not known or not collected by the Zürich observatory can help in completing the S N database, either with entirely new series from other observers or by extending and revising original series partly collected in Zürich. For instance, we can cite the sunspot catalog of the Madrid Observatory  (Aparicio et al. , 2018)  and sunspot-count series from dedicated Japanese observers like Hisako Koyama  (Hayakawa et al.
Therefore, a full understanding of the scale stability before the Wolf-Wolfer transition described above (Section 2. 1. 2) requires a revision and extension of known data series, like the recent recounting of sunspots from the original high-quality synoptic maps by Richard Carrington over 1853 -1861  (Bhattacharya et al. , 2021). One important goal is to fix the scale transfer between Schwabe, the last link of historical observations, and Wolfer, the first modern long-duration sunspot observer. In the eighteenth century, the data-recovery effort largely merges with the one for the group number (see Section 2. 2. 1 below) with the extra requirement that for the S N we need the spot counts in addition to the group counts that were already collected in the G N database  (Vaquero et al. , 2016).
They also give finer diagnostics to understand how the observations were made and their resulting quality. For modern times, annotated drawings indicate how group splitting was accomplished. The recovery of sunspot observations, and sunspot drawings in particular, is now essential as the current revision efforts shift from correction of existing time series to full reconstruction from raw data. The development by  Hoyt, Schatten, and Nesme-Ribes (1994)  and  Hoyt and Schatten (1998a,b)  of the group-number time series was accompanied by the creation of a G N database that was revised and updated by  Vaquero et al. (2016). The open-source V16 data makes it possible to apply different methodologies to compose G N time series. As a related development, within the past decade, the Historical Archive of Sunspot Observations (HASO; haso.
(a) The earliest sunspot observations: 1610 -1645 Thomas Harriot recorded the earliest sunspot drawing that was based on telescopic observation in 1610. Vokhmyanin, Arlt, and Zolotova (2020) revised Harriot's sunspotgroup number and reconstructed butterfly diagrams on the basis of copies of his original manuscript. Shortly afterward, in 1611, Galilei and Scheiner started their sunspot observations. Galilei's data quality greatly improved after Benedetto Castelli invented a method to project a solar disk on a white paper. This method update has been detected in the comparison of Galilei's data with Harriot's data  (Carrasco, Gallego, and Vaquero, 2020). Sunspot data by Galilei and his contemporaries have been comprehensively analyzed in  Vokhmyanin, Arlt, and Zolotova (2021). Christoph Scheiner was the most active observer before the Maunder Minimum.
1618 -1626. He is the only observer in the V16 G N database for ∼60% of his 185 observation days. From an examination of Malapert's reports from 1620 and 1633,  Carrasco et al. (2019c Carrasco et al. ( , 2019a) )  increased the net number of Malapert's daily observations to 251. Moreover, they determined that while Malapert sometimes drew only a single group in his drawings, he sometimes observed several groups. Therefore, Malapert's group counts, taken from the drawings, are now known to be lower limits. Jean Tardé and Jan Smogulecz recorded sunspot observations in 1615 -1617 and 1621 -1625. Their results had been recorded in their books for sunspots as sunspot drawings and textual descriptions  (Arlt and Vaquero, 2020). These records permit derivations and comparisons with other observers of sunspot-group number and sunspot positions for these periods  (Carrasco et al.
, 2021c). Daniel Mögling was another key sunspot observer in 1626 -1629. Hayakawa et al. (2021c)  exploited his original manuscript in the Universitäts-und Landesbibliothek Darmstadt and confirmed his sunspot observations for 134 days. This study revised Mögling's sunspot-group number as well as those of Hortensius and Schickard. It also derived Mögling's sunspot positions to construct a butterfly diagram. These results filled the data gap in the declining phase of Solar Cycle -12 showing the decay of the sunspot-group number and equatorward migration of the reported groups. Pierre Gassendi conducted sunspot observations in 1631 -1638. Vokhmyanin and Zolotova (  2018 ) have analyzed his publications to revise the sunspot-group number and derive sunspot positions. Hevelius (1647) carried out the last known systematic sunspot records made by any astronomer before the Maunder Minimum for the period 1642 -1645.
On the other hand, comparisons with contemporary eclipse drawings have revealed that significant coronal streamers were apparently missing during the Maunder Minimum, unlike those of the modern solar cycles  (Hayakawa et al. , 2021f) , substantiating a conjecture by  Eddy (1976). The combined observing intervals in the  Hoyt and Schatten (1998a,b)  G N database of Martin Fogelius and Heinrich Siverus, both from Hamburg, spanned the years 1661 -1690, approximately half of the 1645 -1700 core of the Maunder Minimum  (Vaquero and Trigo, 2015). Even after removal from the Hoyt and Schatten database of several full years of continuous reported spotless days for Fogelius and Siverus (implausible because of local weather conditions at Hamburg), the two observers were the 13th and 7th most active observers (from 1661 -1671 (with 318 observations) and 1671 -1690 (1040), respectively) from 1610 to 1715 in V16.
Hayakawa et al. (2021d)  consulted Ettmüller (1693) and compared it with the correspondence of Fogelius in the Royal Society archives, leading to the following proposed changes to the V16 database: (1) a reduction of the number of active days for Fogelius from 26 to 3 and a corresponding (net) reduction for Siverus from 20 to 15; (2) conversion of the dates of several observations from the Julian to the Gregorian calendar; and (3) removal of all "ghost" spotless days (days with no explicit sunspot observations interpreted as spotless days) for both observers, representing 98 -99% of their observations. Sunspot records from the Eimmart Observatory of Nürnberg have been analyzed by  Hayakawa et al. (2021e) , based in part on Chiaki Kuroyanagi's archival investigations. The original logbooks from this observatory have been preserved in the Eimmart Archives in the National Library of Russia (St.
This is the weakest link in the entire sunspot-number time series. Recently, several relatively short-duration observers during this interval have been identified and documented. Johann Beyer's sunspot records in 1729 -1730 have been examined and revised in  Hayakawa et al. (2018a). Pehr Wargentin is the only observer given for 1747 in V16, with group counts reported for 17 days for which drawings are available. Arlt (2018)    Additional data have been acquired from East Asia. Hayakawa et al. (2018c,b)  reported on Japanese astronomers at Fushimi and Edo (current Tokyo) who conducted sunspot observations for 1 day in 1793 and 15 days in 1749 -1750, respectively. These data fill data gaps around the neighborhood of the "lost cycle" conjectured to have occurred during the decline of Solar Cycle 4 in 1784 -1798  (Usoskin et al.
(e) Solar Cycles in the nineteenth century Starting with the nineteenth century and even more in the twentieth century, sunspot data are typically providing clearly separated counts of groups and individual spots. Therefore, those data are as relevant to the S N as to the G N reconstruction, and all the following data sets are thus contributing to the S N database described in Section 2. 1. 1. After the end of the Dalton Minimum, Toubei Kunitomo conducted sunspot observations for 157 days in 1835 -1836. While his sunspot records had been known in the existing datasets  (Hoyt and Schatten, 1998a,b; Vaquero et al. , 2016) , preliminary analyses on the original documents have uncovered 17 additional days with Kunitomo observations in 1835 and one such day in 1836. Kunitomo's sunspot-group number has been revised and the area has been measured by  Fujiyama et al.