dataesr/scientific-paragraphs-categorization huggingface dataset:
Additional metadata New metadata fields are included in the Entity table (see database structure; Figure  1 ) to allow users to select sites with similar environmental conditions and to take account of factors that might influence the interpretation of individual records. These include information on vegetation, land use, land cover, and host rock type above the cave. This information is often missing from publications and was not available from data contributors, so information from data products has been added as additional fields to the database for completeness. Vegetation type and land use information were provided by the original investigators. Information on land use and land cover was taken from the Copernicus Global Land Service Land Cover database (LCC v3. 0. 1 Epoch 2019;  (Buchhorn et al.
, 2021 (Buchhorn et al. , , 2020)) , extracted with a radius of 250 m around the cave site. Information on the https://doi. org/10. 5194/essd-2023-364 Preprint. Discussion started: 13 September 2023 c Author(s) 2023. CC BY 4. 0 License. carbonate/evaporite host rock at the cave sites was taken from the WOKAM database  (Goldscheider et al. , 2020)  extracted with a radius of 1000 m. The database also indicates if the trace element content of the host rock and drip water feeding the speleothem is available (but does not include the actual values). Drip height (i. e. , the distance the drip falls from the ceiling of the cave to the speleothem), and the difference between dripwater and carbonate δ 18 O values are given, based on information provided by the original investigators. The SISAL WG repository now hosts images of the entities (speleothem sections) and maps of cave sites.
New geochemical data and metadata fields The elemental ratio for each trace element and the Sr-isotope data are given in individual tables that contain sample identifiers (sample_id), the measurement value and the measurement precision. The sample_id provides the link to the Sample table and thus links these data to the stable isotope data (Figure  1 , Table  1 ). Metadata for the measurements are stored in the Entity table. For each elemental ratio (Sr/Ca, Mg/Ca, U/Ca, Ba/Ca and P/Ca), the Entity table indicates whether the data are available ("yes/no/other/unknown"), the measurement method, the laboratory standards used and, where applicable, the downsampling methods used. The table also indicates if high-resolution trace element data is available. For Sr-isotopes, the Entity table specifies whether this dataset is available, what measurement method was employed and how the measurement was standardized (Figure  1 , Table  1 ).
SISALv3 now provides a unique, persistent identifier for each speleothem (persist_id) in the Entity table  (Figure 1, Table 1 ). This was needed because there was an increasing issue with non-unique entity names, and to deal with the fact that different datasets from the same stalagmite had different entity_ids (e. g. , for datasets covering different time periods in the same speleothem). Thus, the field entity_id provides a unique identifier for a specific dataset, but not necessarily for a specific speleothem, while the persist_id uniquely identifies the speleothem. The persist_id were created by combining the site_id and entity_name (without special characters). There are 837 unique persist_ids and 901 unique entity_ids in the database.
Changes in existing database fields and options The fields "geology" and "rock age" were moved from the Site table to the Entity table (Figure  1 , Table  1 ). This was done to allow for variability in these parameters within the same cave system, particularly relevant for the interpretation of δ 13 C and https://doi. org/10. 5194/essd-2023-364 Preprint. Discussion started: 13 September 2023 c Author(s) 2023. CC BY 4. 0 License. trace element data. The field "trace elements" (yes/no) in the Entity table was removed as it is now redundant. The field "iso_std" describing the standard used for measurement of δ 18 O and δ 13 C values was moved from the stable isotope tables to the Entity metadata table. A number of options for entries in the metadata fields were changed (Table  2 ). The majority of these changes were additions to the previously available options in light of the entries made in the 'Notes' section to allow for more "metadata-filterable" database mining.
Quality control The SISAL WG has used several levels of quality control (QC) and this practice was continued for SISALv3 (Figure  2 ). The initial data compilation is performed by SISAL regional coordinators (from datasets archived on public repositories or in publications) and/or in liaison with the data contributors into standardized excel workbooks. The first QC level consists in the expert assessment by the SISAL regional coordinators who double-check completeness of entered data and correctness of measurement units where applicable. Standardised unit conversion sheets for common conversions (e. g. degrees-minutesseconds to decimal degrees for site information; atomic ratios to activity ratios for dating information; mg/g to mmol/mol for trace element-to-Ca ratios for trace element information) have been provided to regional coordinators (see repository).
The completed workbook(s) are subjected to a series of automated QC (e. g. , age model matches discreet dating information, hiatuses are placed at the correct depth) by the database managers. If the dataset fails to pass the automated QC, it is sent back to the data contributors and regional coordinators for correction. When the datasets pass automated QC, and no further corrections are necessary, the dataset workbook and auto generated QC figures are sent to the data contributors for final evaluation and approval. The same workflow has been followed for the *. txt trace element datafiles. The new metadata fields of vegetation_type and land_use that have been added to SISALv3 for entities that were included in SISALv2 from publications. Data already included in SISALv2 has been checked, and mistakes / unknowns identified during previous data analysis or during the process of trace element data addition were corrected.
Number of new entities 210 Entities added to pre-existing sites 71 Entities with updated entity. entity_status 33 Entities with altered entity. corresponding_current 1 Entities with altered geology 106 https://doi. org/10. 4 ). This corresponds to ~60% of the known published data. There is a clear regional bias in the database with European entities dominating every elemental ratio (Figure  3 ). The Sr-isotope records are more evenly distributed, with records from every region except Asia and Oceania. Temporal coverage for the combined trace element and Sr-isotope dataset is high during the last 2000 years (~60 entities per 20 year interval) and the Holocene (~60 entities per 250 year interval), and then drops to 20-40 entities per 10,000 year interval for the last glacial cycle (12-120 ka BP, where ka stands for 1000 years and BP for "before present", defined as 1950, Figure  4 ).
Beyond ~120 ka BP, the number of entities gradually decreases until the U-Th dating limit is reached (~640 ka). Where the original measured laser ablation data have been provided by data contributors, these have been made available as *. txt datafiles in the repository (Table  4 ). Forty-six trace element records (Mg/Ca: 15, Sr/Ca: 17, Ba/Ca: 4, U/Ca: 5, P/Ca: 5, Sr-isotopes: 2) are only provided in the original format (*. txt files), either because they could not be converted to mmol/mol or because the trace element data were not measured at stable isotope equivalent depths and were at an insufficiently high resolution for accurate resampling. Additional elements that are not included in the database, but have been submitted by data contributors, are also provided as *. txt files (e. g. , Mn, Fe, Zn, Th, Pb, K, Na).
New stable isotope records SISALv3 provides a significantly expanded oxygen isotope dataset compared to SISALv2 (Table  5 , Figure  5 ), with 831 δ 18 O records from 364 sites, compared to 673 records in SISALv2. The most significant increases in δ 18 O records are in Africa (+38%), Europe (+30%), and the Middle-East (+27%; Table  5 ). SISALv3 contains 338 entities covering the last 2000 years, of which 82 are new (Figure  6 ). As record density begins to decrease with age (Figure  6 ), the spatial distribution is reduced as well. For the Last Glacial Maximum (20 -22 ka BP), SISALv3 contains 96 entities (15 new), while for the Last Interglacial (124 -126 ka BP), only 67 entities are available (16 new). There has also been a significant increase in the number of δ 13 C records added, with 588 records in SISALv3 compared to 430 in SISALv2 (Table  5 , Figure  7 ).
At the regional scale, the biggest increase in δ 13 C records is for Africa (+37%), followed by Asia, the Middle East, and Europe (+31% each, Table  5 ). The δ 13 C record coverage decreases following the same patterns as the trace elements and δ 18 O records (Figure  8 ). extracted from the Copernicus LCC database  (Buchhorn et al. , 2021 (Buchhorn et al. , , 2020) )  with a radius of 250 m around the cave sites. Background shading in the map shows the global karst distribution extracted from the World Karst Aquifer Map (WOKAM,  (Goldscheider et al. , 2020). To allow comparison between the two datasets, the Copernicus LCC vegetation data was grouped into broader categories, e. g. , "deciduous" includes all closed and open broad-leaf and needle forest marked as deciduous. The entries in the database are more detailed.
Funding This study was conducted by SISAL ( Speleothem Isotopes Synthesis and Analysis ), a working group of the  Past Global Changes (PAGES)  project. In this framework, we received financial support from the  Swiss Academy of Sciences  and the  Chinese Academy of Sciences. The design and construction of the SISALv3 database were supported financially by a  PAGES Data Stewardship Scholarship  to F. We also acknowledge funding by  PAGES , the  Minerva Stiftung  (grant  3063000253 ), and the  Institute of Earth Sciences at the Hebrew University Jerusalem (Israel)  for supporting the organisation of a workshop to kickstart the initiative.
https://doi. org/10. 5194/essd-2023-364 Preprint. Discussion started: 13 September 2023 c Author(s) 2023. CC BY 4. 0 License. 210 Figure 2: Quality checking workflow adopted for inclusion of datasets in SISALv3. The colors indicate different quality check levels: blue -data contributing sources (original authors or datasets deposited in repositories and publication supplementary information).
https://doi. org/10. 5194/essd-2023-364 Preprint. Discussion started: 13 September 2023 c Author(s) 2023. CC BY 4. 0 License. 4 Overview of database contents 4. 1 Trace element and Sr-isotope records SISALv3 contains 94 Mg/Ca, 83 Sr/Ca, 51 Ba/Ca, 25 U/Ca, 29 P/Ca and 14 Sr-isotope records (Table.
Acknowledgments We thank  Céline Angleraux  and  Pierre Contard  from the PBES in the SFR biosciences ( UMS3444 ) for animal breeding. We thank  T. Andrieu  and  S. Dussurgey  from the  AniRA-Cytometry  platform in the SFR biosciences ( UMS3444 ) for their expertise in cell sorting, and  D. Ressnikoff  and  B. Chapuis  ( CIQLE imaging center, SFR Santé Lyon-Est  ( UMS3453 ) for their help with image acquisition. We also thank  R. Mounier  for critical reading the manuscript. This study was funded by  Association Francaise contre les Myopathies (AFM)  through  MyoNeurAlp alliance and by  grant  ANR-11-BSV2-017-01  and 'equipe FRM' grant from the  Fondation pour le Recherche Medicale  to L. S.
Patient assessment and selection Assessment and selection of FT candidates is a key challenge for FT policy and practice. FT teams at different institutions have proposed valuable tools, although a shared set of criteria has not been established yet. 7, 8  Lack of standardization in patient selection is partly due to the small number of patients involved and also a result of lack of standardized measures for outcome assessment and inadequate outcome data sets. FT stakeholders agreed on the need to develop standardized protocols for evaluation of candidate suitability for FT. According to the panel, a thorough evaluation of FT candidates should be handled by multidisciplinary teams. Besides the assessment of the clinical status, the individual dimension should be investigated, including patient psychological status, distress, and self-perception.
Acknowledgments This work was supported by  NSF CRCNS/DARE  grant  2113069  (Ausborn, Rybak),  NIH/NINDS  grant  R01 NS110550  (Rybak),  NIH/NINDS  grant  R01NS112304  (Danner),  NIH/NINDS  grant  R01NS115900  (Danner),  CNRS ,  Agence Nationale de la Recherche  ( ANR-21-NEUC-0001  and  ANR-20-CE16-0026 ) and  Fondation pour la Recherche Médicale  (FRM,  EQU202203014620 ) (Bouvier).
LI. CA) database  [16, 17]. Consequently, economic evaluations based on RCT data alone may have different outcomes than those based on real-world data. [18]  It is therefore crucial to understand the outcomes and costs of technologies in the RW, their relative effectiveness versus comparator technologies, and to bring this information to the attention of both clinicians and health technology assessment (HTA) agencies so that the reimbursement decisions are informed by the best possible evidence leading to efficient allocation of resources. To date, no head-to-head comparisons of TARE versus AB have been undertaken in HCC patients, meaning there is an evidence gap when assessing the best possible treatment course for eligible HCC patients. An indirect comparison suggested that TARE using Y-90 resin microspheres and AB may achieve similar quality of life (QOL) outcomes, but no studies have compared efficacy or effectiveness outcomes of these two technologies.
Data sources Individual patient-level data (IPD) from patients who had TARE in the SARAH trial and published, aggregate data from the single-arm, observational AB-real study as published by D'Alessio et al. were used. [10, 14]  Because there was no common comparator, an unanchored matching-adjusted indirect comparison (MAIC) was conducted to compare TARE using Y-90 resin microspheres with AB, adjusting for between-study differences in key variables that are considered to be prognostic or effect modifiers. The analysis followed the National Institute for Health and Care Excellence (NICE) Decision Support Unit guidelines for population-adjusted indirect comparisons and was performed in R (version 4. 1. 2). [20]  Protocol and ethical approval for the SARAH study was granted by the Comité de Protection des Personnes Ile de France XI and all patients provided written informed consent.
[14]  The baseline characteristics of the patients included in the study by D'Alessio et al. were more aligned with the baseline characteristics of patients in the SARAH trial compared with other data sources available in the literature such as the IMbrave150 RCT. The indirect comparison between SARAH and D'Alessio et al. was deemed to generate more relevant results than comparing, for instance, SARAH versus IMbrave150. Key variables demonstrated to be prognostic factors of survival (e. g. , albumin-bilirubin [ALBI] grade, presence of macrovascular invasion or aetiology) were considerably closer between the SARAH and D'Alessio et al. populations, compared with the IMbrave150 population (Table  1 ; Supplementary Table  1 ). A side-by-side comparison of the included studies showed that the majority of baseline characteristics were balanced across treatment arms, with some exceptions: geography of included patients as only French patients were included in SARAH; the proportion of patients with hepatitis B and C as cause of disease was lower in the SARAH trial (as opposed to the proportion of patients with alcohol as the cause of disease); patients with macrovascular invasion (MVI) was higher in SARAH, but the MVI definition was also larger in the RCT compared to the AB-real study; the number of unsuccessful TACE prior to the studied treatment was also higher in SARAH; and the proportion of patients with extrahepatic spread was 38% in the study by D'Alessio, while this was considered an exclusion criterion in SARAH (except lung tumours <1 cm and lymph nodes <2 cm; Table  1 ).
[26, 27]  The base case analysis was conducted using the per protocol (PP) patient population in SARAH, as this was considered more appropriate by NICE during the technology appraisal of TARE. [28]  According to the NICE Assessment Group, there was a substantial proportion of patients who failed the work-up procedure and did not subsequently receive treatment with TARE and therefore the PP population was deemed more suitable. [28]  The intention-to-treat (ITT) population was used in scenario analyses. Patients with incomplete data were removed to generate the final dataset. The baseline characteristics of patients in the SARAH trial were reweighted via the method of moments. Reweighted data from SARAH reflected the characteristics of patients receiving treatment with AB in the RW and were therefore used to indirectly compare OS, PFS and response rates between TARE and AB.
[7] [8] [9] [10] [11] [12] [13] [14]  The approach adopted for the current analysis, however, might help to reduce this efficacy-effectiveness gap. Even though aggregate data from published RCTs are commonly used for MAICs, in the current analysis aggregate data from a RW study were used for AB for two reasons. First, and the key reason driving the analysis approach, IMbrave150 RCT was not deemed appropriate because marked differences exist between the SARAH and IMbrave150 RCTs: the studies were conducted across different geographies, consequently capturing patients with different baseline characteristics such as disease aetiology and vascular extension which are likely to have influenced the results in each of the studies. [10, 12]  Secondly, an indirect comparison of SARAH and IMbrave150 may not be that relevant and that the study by D'Alessio et al.
is closer to the characteristics of patients in the SARAH RCT and is also likely to better reflect the effectiveness of AB in the RW patient population. [10, 14]  The SARAH RCT and the AB-real study by D'Alessio et al. were therefore selected as data sources, maximising the power of the analysis and minimising the uncertainty associated with the results. This is a strength of the analysis and is expected to facilitate well-informed decision-making by clinicians and payers by shrinking the efficacy-effectiveness gap. Other key strengths of this analysis include the availability of patient-level data from the SARAH RCT; the reconstruction of patientlevel data from the RW data on AB using state-of-the-art statistical techniques;  [21]  and a thorough review of the literature for the identification of potentially relevant confounders.
[22, 23, 26, 27]  Finally, the study by D'Alessio et al. had a considerably larger sample size and covered a wider geography than other RW studies like the one by De Castro et al. , so the selected study might have resulted in more robust effectiveness estimates. [13, 14]  Additionally, the AB-real study reported more conservative effectiveness estimates than De Castro et al. (which reported median OS and PFS of 10. 8 and 5. 1 months, respectively), so the results presented here could actually be considered conservative. [13, 14]. This study also had some limitations. There were inevitable differences between study designs, one data source being an RCT and the other an observational study; however, the adopted methodology for adjustment minimised the risk of bias. Regarding patients' baseline characteristics, the current analysis considered that a higher proportion of patients had macrovascular invasion in SARAH compared with the RW study (63% versus 40%).
This could potentially have impacted the survival analyses as a worse liver function acts as a competitive cause of death. This analysis adds new insights on comparative efficacy to the recent study indicating that TARE and AB may achieve similar QOL outcomes, but unfortunately a comparison of the safety profile could not be conducted for technical reasons. [19]  The way D'Alessio et al. reported safety events could not be replicated using IPD from SARAH and the lack of access to the IPD from the RW study was an unavoidable limitation. Therefore, a gap in the evidence still remains. Finally, patient-level data from Y-90 resin microspheres registries would have allowed a more sophisticated analysis resulting in more robust results, but unfortunately these were not available to the authors. Given that registries of Y-90 resin microspheres have shown substantially better outcomes in RW patients compared with the SARAH trial, added to the fact that other RW studies not used here have shown worse effectiveness outcomes for AB, the results presented here might represent conservative estimates of the true values.
Ethics approval Individual patient-level data from SARAH and published, aggregate data from the study by D'Alessio et al. were used for this analysis. Protocol and ethical approval for the SARAH study was granted by the Comité de Protection des Personnes Ile de France XI and all patients provided written informed consent. Protocol approval was granted to D'Alessio et al. by the Imperial College Tissue Bank (R16008) and locally by the ethical committee of each participating site; informed consent was not considered necessary by the review committee due to the retrospective nature of the study. Both studies were done in accordance with the provisions of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use Guidelines for Good Clinical Practice and the Declaration of Helsinki.
Acknowledgements DJP is supported by grant funding from the  Wellcome Trust Strategic Fund  ( PS3416 ), the  Associazione Italiana per la Ricerca sul Cancro  ( AIRC MFAG 25697 ) and acknowledges grant support from the  Cancer Treatment and Research Trust (CTRT) , the  Foundation for Liver Research  and infrastructural support by the  Imperial Experimental Cancer Medicine Centre  and the  NIHR Imperial Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the  NIHR , or the  Department of Health and Social Care.
Acknowledgements We would like to thank our colleagues  Ms. Sarah Durand ,  Ms. Marine Oudot , and  Dr. Emilie Crouchet  ( Inserm UMR_S1110, Strasbourg, France ) for excellent technical support, and  Ms. Anne Zeter  ( Inserm UMR_S1110, Strasbourg, France ) for excellent administrative support. We also acknowledge our colleagues  Dr. David Durantel  ( CIRI, Lyon, France ) and  Dr. Joachim Lupberger  ( Inserm UMR_S1110, Strasbourg, France ) for scientific advice and support. We thank  Prof. Olivier Schwartz  ( Institut Pasteur, Paris, France ) for the  S-Fuse  cells,  Dr. Feng Zhang  ( Broad Institute of MIT and Harvard, Cambridge, MA, USA ) for the lentiCRISPR v2 plasmid,  Prof. Franck V. Chisary  ( The   Scripps Research Institute, La Jolla, CA, USA ) for the Huh7. 5. 1 cells,  Prof. Eberhard Hildt  ( Paul-Ehrlich-Institut, Langen, Germany ) for the HepAD38 cells, and  Prof.
Financial support This work of the  Interdisciplinary Thematic Institute IMCBio , as part of the  ITI 2021-2028 program  of the  University of Strasbourg ,  CNRS  and  Inserm , was supported by  IdEx Unistra  ( ANR-10-IDEX-0002 ), and by  SFRI-STRAT ' US  project ( ANR-20-SFRI-0012 ) and  EUR IMCBio  ( ANR-17-EURE-0023 ) under the framework of the  French Investments for the Future Program. E. R. V and J. L. acknowledge fundings from  Inserm  and the  Agence Nationale de Recherches sur le Sida et les Hépatites Virales (ANRS | Maladies Infectieuses Emergentes , grant numbers  ECTZ104527 ,  ECTZ208589 ,  ECTZ102776 , and  ECTZ174555 ). E. R. V.