dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Availability Statement All model outputs from the CMIP6 DECK and the standard CFMIP experiments are freely accessible at https:// pcmdi. llnl. gov/CMIP6/ or at https://esgf-node. llnl. gov/projects/esgf-llnl/. All graphics have been produced using the NCAR NCL software freely accessible at https://www. ncl. ucar. edu/.
CHEOPS photometry The CHEOPS space telescope carried out two transit observations of TOI-1055 b, the first on 25 May 2021 (file key: CH_PR100024_TG012301_V0200) and the second one on 11 June 2021 (file key: CH_PR100024_TG012302_V0200). CHEOPS photometry was processed using the dedicated data reduction pipeline  (version 13. 1; Hoyer et al. 2020) , and is available via the Data & Analysis Center for Exoplanets (DACE) database 2. We discarded data points with bad quality flags and applied a 5-MAD-clipping to reject outliers; the raw CHEOPS LCs are shown in Fig. A. 1. To identify and correct for systematics affecting CHEOPS LCs, the data also contain vectors reporting the temporal evolution of the telescope roll angle (roll, for a complete discussion see  Bonfanti et al. 2021) , flux of background stars inside the photometric aperture (contamination), smearing effect (smear, seen as trails on the CCD), background light (bg, e.
The bp algorithm detected one change point location at the 12th observation (BJD ∼ 2456165. 6 corresponding to 26 August 2012, that is, within the HARPS-pre dataset), dividing the HARPS-pre RV measurements in two piecewise stationary segments. Since the change in the coefficients of correlation of RV against (FWHM SN , A, γ) is judged to be statistically significant (∆BIC ≈ -8 in favour of that change point location), that date likely marks an inflection point in the stellar activity cycle with which (FWHM SN , A, γ) are supposed to be correlated. The RV detrending baseline we applied to each segment is a polynomial of the following form RV = β 0 + k t k=1 β k,t t k + k F k=1 β k,F FWHM k SN + k A k=1 β k,A A k + k γ k=1 β k,γ γ k , (1) where the β parameters are the polynomial coefficients and ) for the two different piecewise stationary segments found within the HARPSpre dataset.
In the case of the TESS LCs, the PDCSAP flux does not correlate with any of the variables provided in the SPOC data product. The two LCs extracted from Sector 13 only require a first-order polynomial to detrend flux against time, t, while the baseline function to be applied to the TESS LC from Sector 27 is a scalar (i. e. flat line). Similarly, we evaluated the photometric baseline for each of the CHEOPS LCs and the RV baseline according to Eq. (  1 ). The detrending models employed for the joint LC and RV analysis are listed in Table  A. 2. We launched a preliminary longer run to evaluate the possible rescaling of the photometric errors, as detailed in  Bonfanti & Gillon (2020) , and obtain reliable error bars on the fitted parameters. Finally, we performed the global MCMC analysis employing four chains of 300 000 steps each, adding two RV jitter terms to account for any instrumental noise not included in our nominal uncertainties and/or possible sources of stellar variability not removed by our method.
84 +0. 54  -0. 49 ρ , which is consistent with our adopted ρ at the 1. 4σ level. From the RV analysis, we obtained K b = 5. 03 +0. 60 -0. 59 m s -1 (detection at ∼8σ level), which implies a planetary mass of M b = 20. 4 +2. 6 -2. 5 M ⊕ and a mean density of ρ b = 2. 65 +0. 37 -0. 35 g cm -3. Figure  2  shows the phase-folded RV curve of TOI-1055 b. The SN-fit-based extraction of RV data, the application of the breakpoint analysis, and the additional 16 HARPS spectra enabled us to obtain a firm planetary mass measurement, with a significantly increased precision when comparing our results with the literature (see Table  3 ). We also performed the analysis with a more standard approach based on directly taking the data as released from the HARPS Data Reduction Software (DRS) and applying a polynomial detrending within the MCMC framework.
The results agree well within 1σ with those obtained from the SN-fit and L8, page 4 of 13 bp-based analysis, but the K b detection is at the ∼7σ level (compared to the ∼8σ level obtained using our novel technique), with K b,DRS = 5. 05 +0. 71  -0. 69 m s -1. Furthermore, after accounting for the jitter terms, the RV average error bars are larger than those obtained from our reference analysis by a factor of ∼2 and ∼1. 2, respectively, for the HARPS-pre and HARPS-post datasets. To further test our novel technique, instead of summing up all the order-by-order individual CCFs to get one global CCF per epoch, we built two different CCFs per epoch (CCF blue and CCF red ) by summing up all those individual CCFs derived from the first and the last 44 orders of the spectrograph, respectively. Then we extracted two different RV values per epoch by applying a SN-fit onto the two series of CCF blue and CCF red , obtaining two different RV time series (RV blue (t) and RV red (t), respectively).
After performing two different joint analyses, as described in Sect. 4. 2, but inputting the RV blue (t) (resp. RV red (t)) time series, we obtained K b,blue = 4. 94 ± 0. 86 m s -1 (resp. K b,red = 4. 73 ± 0. 88 m s -1 ), which agree well within 1σ with the K b value of our reference analysis. Moreover, the rms of the RV residuals for the HARPS-pre and HARPS-post data resulted to be rms blue = (3. 5; 2. 7) m s -1 and rms red = (2. 5; 2. 4) m s -1 , where the higher rms blue values agree with expectation for which the line-profile distortion caused by stellar spots is higher at bluer wavelengths (e. g Jeffers et al. 2022). T eq (a) [K] 752 ± 10 R b [R ⊕ ] 3. 490 +0. 070 -0. 064 M b [M ⊕ ] 20. 4 +2. 6 -2. 5 ρ b [g cm -3 ] 2. 65 +0. 37 -0. 35 Notes. ( a) Assuming zero albedo. Following our SN-fit extraction and bp analysis, the mass we obtained is consistent within 1σ with that found by P21.
41 +0. 34  -0. 20 M ⊕ and a thickness of 1. 05 +0. 30  -0. 29 R ⊕ , while the water content is unconstrained. The additional RV measurements and, particularly, the SNfit-based RV extraction and the use of the bp algorithm lead to a determination of the mass of TOI-1055 b which is significantly more precise than the value previously published in the literature. Our results show that the SN fit combined with the bp technique enables an efficient cleaning of the RV time series from stellar activity, providing a firm detection of the Doppler reflex motions induced by orbiting planets. 1 ); the digit in the subscript refers to the polynomial order). Each panel compares the optimal detrending coefficients applied to the two different piecewise stationary segments that were found within the HARPS-pre dataset.
Comparison of the planetary radius, R b , mass, M b , RV semiamplitude, K b , and average RV uncertainties accounting for the jitter, σ RV+jitter , as derived across the range of studies considered in this workmeasurements are (2. 86; 3. 77) and (5. 29; 5. 76) m s -1 for P21 and G21, respectively. Following our analysis, the average RV errors after accounting for jitter terms are sensibly lower, being (1. 29; 2. 33) m s -1 for the HARPS-pre and HARPS-post datasets. Following the log R HK -jitter relation ofHojjatpanah et al. (.
Acknowledgements. CHEOPS is an ESA mission in partnership with Switzerland with important contributions to the payload and the ground segment from  Austria, Belgium, France, Germany, Hungary, Italy, Portugal, Spain, Sweden , and the  United Kingdom. The CHEOPS Consortium would like to gratefully acknowledge the support received by all the agencies, offices, universities, and industries involved. Their flexibility and willingness to explore new approaches were essential to the success of this mission. We thank the anonymous referee, whose valuable comments have improved the quality of the manuscript. DG gratefully acknowledges financial support from the  CRT foundation  under Grant No. 2018. 2323"Gaseousor rocky?Unveiling the nature of small worlds". JAEg and YAl acknowledge the support of the  Swiss National Fund  under grant  200020_172746.
ML acknowledges support of the  Swiss National Science Foundation  under grant number  PCEFP2_194576. SS have received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No  833925 , project  STAREX ). S. G. S. acknowledges support from  FCT  through  FCT  contract nr. CEECIND/00826/2018  and  POPH/FSE (EC). TWi and ACCa acknowledge support from  STFC  consolidated grant numbers  ST/R000824/1  and  ST/V000861/1 , and  UKSA  grant number  ST/R003203/1. The Belgian participation to CHEOPS has been supported by the  Belgian Federal Science Policy Office (BELSPO)  in the framework of the  PRODEX Program , and by the  University of Liège  through an  ARC grant for Concerted Research Actions  financed by the  Wallonia-Brussels Federation.
L. D. is an F. R. S. -FNRS Postdoctoral Researcher. This work has been carried out within the framework of the  NCCR PlanetS  supported by the  Swiss National Science Foundation  under grants  51NF40_182901  and  51NF40_205606. LMS gratefully acknowledges financial support from the  CRT foundation  under Grant No. 2018. 2323'Gaseous or rocky?Unveiling the nature of small worlds'. We acknowledge support from the  Spanish Ministry of Science and Innovation  and the  European Regional Development Fund  through grants  ESP2016-80435-C2-1-R ,  ESP2016-80435-C2-2-R, PGC2018-098153-B-C33 ,  PGC2018-098153-B-C31 ,  ESP2017-87676-C5-1-R , MDM-2017-0737  Unidad de Excelencia Maria de Maeztu-Centro de Astrobiología (INTA-CSIC) , as well as the support of the  Generalitat de Catalunya/CERCA  programme.
D. S. D. is supported in the form of work contract ( DL 57/2016/CP1364/CT0004 ) funded by national funds through FCT. B. -O. D. acknowledges support from the  Swiss State Secretariat for Education, Research and Innovation (SERI)  under contract number  MB22. 00046. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (project  Four Aces. grant agreement No  724427 ). It has also been carried out in the frame of the  National Centre for Competence in Research PlanetS  supported by the  Swiss National Science Foundation  (SNSF). DE acknowledges financial support from the  Swiss National Science Foundation  for project  200021_200726. MF and CMP gratefully acknowledge the support of the  Swedish National Space Agency  ( DNR 65/19 ,  174/18 ).
M. G. is an F. R. S. -FNRS Senior Research Associate. SH gratefully acknowledges CNES funding through the grant  837319. KGI is the  ESA   CHEOPS  Project Scientist and is responsible for the  ESA CHEOPS Guest Observers Programme. She does not participate in, or contribute to, the definition of the  Guaranteed Time Programme  of the CHEOPS mission through which observations described in this paper have been taken, nor to any aspect of target selection for the programme. This work was granted access to the HPC resources of MesoPSL financed by the  Region Ile de France  and the project  Equip@Meso  (reference  ANR-10-EQPX-29-01 ) of the programme Investissements d'Avenir supervised by the  Agence Nationale pour la Recherche. PM acknowledges support from  STFC  research grant number  ST/M001040/1.
paracholerae  15. We subdivided V. cholerae genomes into 11 clades, referred to henceforth as VcA to VcK (Fig. and Supplementary Table  5 ). VcH contained all 7PET epidemic lineage genomes utilized in this dataset, including the majority (216/232) of the Yemen 2018-2019 genomes and all 42 previously reported 2016-2017 Yemeni genomes  7  (Extended Data Fig. 4 ). Although Yemeni VcH isolates show limited genomic diversity (99. 98%-100. 00% average nucleotide identity (ANI) similarity; 0 to single nucleotide polymorphisms (SNPs)), the remaining 16 Yemeni genomes belonged to clades V. paracholerae (Vpc), VcD and VcK, and were overall more diverse than VcH isolate genomes (96. 24%-99. 99% ANI similarity) (Fig. 1  and Table  1 ); these represent 'non-7PET' lineages. Among these, we found five distinct sequence types in three lineages: Vpc (n = 1; ST1499), VcD (n = 21; ST555, ST1020 and ST1498) (Supplementary Table  5 ) and VcK (n = 2; ST170) (Fig.
Genome variation of VcH. 9 (7PET-T13) isolates in Yemen Given the change in antimicrobial susceptibility seen in the 2018-2019 Yemen isolates, we compared in detail the VcH. 9 isolate genomes from Yemen with each other and with related isolates taken elsewhere. We identified 3, 4 and 21 fixed SNPs in the crown clade containing VcH. 9. e,f,g,h, the clade containing VcH. 9. g,h, and VcH. 9. h, respectively (including 2, 2 and 11 non-synonymous SNPs, respectively) (Supplementary Table  8 ). Changes fell largely within genes predicted to be involved in carbohydrate metabolism, signal transduction and chemotaxis, none of which could be directly linked to change in virulence (Supplementary Table  8 ). Previously, the 2016-2017 Yemeni isolates carried an SXT ICE differing by only three or four SNPs from the ICEVchInd5/ICEVchBan5 reference sequence (GenBank accession GQ463142.
Distribution and relatedness of MDR MGEs Analysis of the broader phylogenetic context of pCNRVC190243 and associated YemVchMDRI showed that the plasmid was also present in three VcD (ST1499 and ST1020) and two VcK (ST170) isolates collected in 2019 in Yemen. Comparing the full-length sequence of all pCNRVC190243 plasmids from VcH. 9, VcK and VcD isolates showed that all sequences were identical except for two isolates: one varied by a single SNP resulting in an amino acid change S71F in the sulphonamide resistance protein Sul1 (YE-NCPHL-19105; G26720A SNP); the other by a single intergenic SNP. We also found the YemVchMDRI element integrated into chromosome 2, without the pCNRVC190243 backbone, in all 18 of the ST555 isolates (Fig. 1  and Supplementary Text). More broadly, by searching the public genome databases (Supplementary Table  10 ), we found related but non-identical elements in other V.
cholerae: an IncC plasmid, named pYA00120881 (GenBank accession MT151380), was identified in 13 closely related VcH. 9. a and VcH. 9. c isolates (Fig. 2a ) that were collected in 2018 in Zimbabwe  16. The backbones of pCNRVC190243 and pYA00120881 share 99. 98% nucleotide sequence identity, but pYA00120881 carries a different MDR genomic region-featuring a bla gene encoding a CTX-M-15 extended spectrum beta-lactamaseinserted at the same locus (Extended Data Fig. 8 ). Furthermore, 59 V. cholerae O139 (ST69) isolates collected in China from 1998 to 2009 (publicly available genomic data released in BioProject PRJNA303115)  21, 22  carry IncC-type plasmids that show similarity to pCNRVC190243 and also include YemVchMDRI-like PCT elements, albeit lacking ISCR1 and the bla PER-7 gene. Importantly, when using the YemVchMDRI sequence alone to search the database (Supplementary Table  11 ), we found that the genome of V.
9) derived from a single introduction. From the inferred phylogeny we were able to subtype Yemeni 7PET-T13 genomes into four different phylogenetic clusters that dominated at different points in time during the outbreak. We observed two large clonal expansions for the sister clades that dominated in 2018 and 2019, both of which first emerged in early 2017. Our data showed that the switch in AMR phenotype coincided with the appearance in late 2018 of plasmid pCNRVC190243 in isolates belonging to the 2019 VcH. 9. g phylogenetic cluster. Plasmid pCNRVC190243 carries the PCT YemVchMDRI, which in turn comprises a type 1 integron and the ISCR1 blaPER-7 element. YemVchMDRI confers resistance to third-generation cephalosporins, streptomycin (and spectinomycin), macrolides and sulphonamides, plus disinfectant tolerance provided by the qac gene  24.
Importantly, pCNRVC190243 (carrying the PCT YemVchMDRI) was also found in a small number of different non-7PET isolates from Yemen collected in 2018-2019 as well as the only VcH. 9. h isolate taken in 2019. Although the plasmid pCNRVC190243 carrying the PCT YemVchM-DRI appears to be a novel composite element, plasmid pYAM00120881, identified in VcH. 9 V. cholerae isolates from Zimbabwe in 2018  16  , shares an almost identical plasmid backbone, albeit one lacking PCT YemVch-MDRI. Conversely, although rare in the public databases, elements highly similar to YemVchMDRI occurred in diverse lineages including: V. cholerae O139, V. cholerae ST555 and two A. baumanii strains. Detailed comparison of these PCT-related elements suggests they all are derived from a common ancestral element, and the presence of PCT YemVchMDRI in multiple ST555 strains isolated from different geographical origins suggests this element is widely distributed and has been acquired multiple times by this and other V.
9. g isolates was followed by its dramatic spread, a clonal expansion that we show occurred in 2018, a time when the treatment regimen was to treat symptomatic cases with macrolides. It is possible to explain the distribution of pCNRVC190243 by multiple acquisitions of the plasmid from independent sources or, more parsimoniously, as direct horizontal gene transfer events between the epidemic and endemic V. cholerae strains. The large population sizes attained by the epidemic lineages in Yemen make spillover from the dominant cluster at the time, VcH. 9. g, probable. Consistent with this, our microbiology, serotyping and sequencing data showed that four of the samples analysed here contained both ST555 and 7PET strains (Supplementary Text), indicative of a limited number of mixed infections from individual patients.
Genome assembly and annotation The 260 sequencing read sets produced at the WSI (Extended Data Fig. 3 ) were processed with the WSI Pathogen Informatics pipeline  34  ; quality of sequencing runs was assessed based on quality of mapping of 10% reads to the genome of reference strain N16961 (GenBank Assembly accession GCA_900205735. 1) using the Burrows-Wheeler Aligner  35  ; read sets passed the check if at least 80% bases were mapped after clipping, the base and indel error rate were smaller than 0. 02, and fewer than 80% of the insert sizes fell within 25% of the most frequent size. Contamination was assessed manually based on Kraken classification of reads using the standard WSI Pathogen reference database, which contains all viral, archaeal and bacterial genomes and the mouse and human reference published in the RefSeq database as of 21 May 2015 (Supplementary Table  4 ).
Contextual genomic data To provide phylogenetic context, we also included in this analysis previously published genome sequences from a globally representative set of isolates ('assembled V. cholerae genomes' dataset; n = 882). We first gathered genome assemblies generated at the WSI using the pipeline described above based on previously published short reads sets from V. cholerae isolates belonging to sub-lineage T13 of 7PET Wave 3 (7PET-T13) and from strains isolated in the close spatio-temporal context that is within a decade in Africa and South Asia (where the ancestor of T13 is thought to originate  7  ). These include all 42 Yemen 2016-2017 isolates  7  , 103 recent isolates from East Africa including from Kenya 7 , Tanzania  41  , Uganda  42  and Zimbabwe  16  , and 74 isolates from South Asia  43.
In addition, we included genomes spanning the wider diversity of V. cholerae, including all 119 genomes from China  44  , as well as 312 genomes from the collections of contextual genomes used in our previous studies  7, 33. Together with the 232 Yemen 2018-2019 isolate genome assemblies (see above), our final dataset consisted of 882 assembled V. cholerae genomes (Supplementary Table  5  and Extended Data Fig. 3 ).
Characterization of genomic features of interest We first predicted the presence of various genomic features by searching genomes against reference databases. The presence of AMR genes, plasmid replicon regions or virulence factors were predicted using ABRicate  45  , searching the reference databases NCBI AMR+  46  , Plasmidfinder  47  or VFDB  48  , respectively. We searched for the presence of conjugation apparatus (as a sign of plasmids or ICEs) and CRISPR-Cas arrays and subtyped these systems using MacSyFinder (v. 2. 1)  49  with models CONJScan (v. 2. 0. 1) and CasFinder (v. 3. 1. 0). Genomes positive for Cas systems were further analysed with CRISPRCasFinder 50 on the Pasteur Institute Galaxy server to retrieve CRISPR arrays. In addition, we searched for sequences with significant similarity to previously described mobile elements relevant to our study.
BLASTN  51  (v. 2. 7. 1+, with default parameters) was used to identify known MGEs: the SXT ICE ICEVchInd5 (GenBank accession GQ463142. 1); ICP1-like vibriophages ICP1_VMJ710 and ICP1_2012_A (GenBank accessions MN402506. 2 and MH310936. 1, respectively)  52  and the ICP1-like Vibrio phage YE-NCPHL-19021, which genome was the only assembled contig from the reads obtained from sample YE-NCPHL-19021 (this study; GenBank accession MW911613. 1); the IncC-type plasmid pCN-RVC190243, obtained from the hybrid assembly of strain CNRVC190243 described above (this study; ENA sequence accession OW443149. 1); the MDR PCT YemVchMDRI, extracted from this plasmid (positions 16,442 to 36,862); PICI-like elements (PLE) 1, 2 and 3 (GenBank accessions KC152960. 1, KC152961. 1, MF176135. 1)  53, 54. Absence of elements was verified at the read level as described below.
In silico classification of V. cholerae To predict the antigenic serogroup, we used BLASTN to screen the assemblies against a reference database of sequences of lipopolysaccharide O-antigen biosynthetic gene clusters that were delineated in the genome of reference strains for each known serogroup  57. Best reference locus matches were identified as those with the highest combined score, summing scores of all local alignments, except when multiple local alignment overlapped in which case only best-scoring alignments were retained  58. For O1 serotype prediction (Inaba or Ogawa), we used a combination of approaches including BLASTN search against the 882 assembled V. cholerae genomes (as described above) and ARIBA 59 v. 2. 14. 6+ (with default parameters) to screen the sequencing read sets against the wbeT gene sequence from strain NCTC 9420 (positions 311,049-311,909 of GenBank accession CP013319.
Identification of single nucleotide variants For variant calling, Illumina short reads from 7PET and VcD genomes were mapped against the reference genomes from strains CNRVC190243 and CNRVC190247, respectively (456 'mapped 7PET genomes' and 33 'mapped VcD genomes' datasets, respectively), and all genomes were mapped against the in-house MGE database described above. We mapped all 260 short-read sets from 2018-2019 Yemeni isolates sequenced at the WSI, including those 28 read sets that assembly showed low coverage or appeared contaminated with phage genomes (Supplementary Table  4 ); to recover variation data evidenced at the read level, provided reads were mapped at a sufficient depth (see below). We also mapped read sets from the 21 strains sequenced at the IP, and from contextual isolates of the 7PET-T13 sub-lineage and close relatives (Contextual genomic data), for a total of 468 mapped genomes.
Reads were trimmed with Trimmomatic, mapped to both CNRVC190243 reference chromosomes with BWA-MEM and the IncC plasmid pCNRVC190243. Mapped genomes with an average read depth below 5× over the two chromosomes were deemed of insufficient read depth and were excluded (12 read sets mapped to CNRVC190243, all from this study and generated at WSI, were excluded for a final set of mapped 7PET genomes (Supplementary Table  5 ); no read set mapped to CNRVC190247 was excluded). We used the software suite samtools/ bcftools 61 v. 1. 9 to call single nucleotide variants with a minimum coverage of 10× read depth. Resulting consensus sequences were combined into a whole-genome alignment, which was processed with snp-sites to produce an SNP alignment. Overall genome similarity was assessed by computing SNP distances based on the above alignments using the function 'dist.