dataesr/scientific-paragraphs-categorization huggingface dataset:
It is important to note that the presence of the ISO-9001 system in a database does not mean that the submitted data are of the required quality and uploading does not improve the dataset quality. On the other hand, if ISO-9001 compliant quality measures are in place during uploading, prompting the user to submit information on the processes/workflows and standards used for data creation, they will force the submitting party to add information that may have been initially omitted. In terms of metadata and semantic annotation, most of the databases that responded to the questionnaire require the submission of all types of metadata, although a QA/AC tool for metadata is currently lacking from all except the S 2 Nano database. S 2 Nano has implemented scoring systems like the INFO score from bibliographic metadata (journal name, journal information, etc.
), PChem and Tox scores from technical metadata (the methods and protocols used to produce the data, instrument details and settings). Generally, there was consensus among the database owners that the most common challenge is to gather the necessary metadata, especially in a standardised format further emphasising the need for a metadata standard for nanosafety research. At the same time, there needs to be a balance between strict standardisation and allowing users the necessary freedom to fully represent their data. This is why some fields are not mandatory, which results in databases relying on the willingness of users to fill in all the required information and the increased difficulty to create inter-dependencies between metadata information for complex workflows. Most of the surveyed databases have some form of metadata functionality to promote data interoperability, combination and reusability via higher quality and bigger datasets.
Ontologically, most databases (4/6) use either specific ontologies (e. g. , eNM, NPO) or one of the available lookup services (e. g. , EMBL-EBI, NanoCommons). The use of lookup services instead of specific ontologies results from the fact that terms may be missing specific definitions when added into or inherited between different ontologies. Another issue is the context-specific definition of terms and reuse. In such cases, the correct term may be identified in various ontologies, but the definition may change based on field-specific usage. This creates significant uncertainties pertaining to the applicability of a specific term for the annotation of specific (meta)data and is one of the main issues data curators and database owners face. However, some of the difficulties with the use of more general ontological services is the uncertainty of which term to use when that term is listed in several repositories.
Metadata Awareness and Training It is not by chance that all responders named metadata acquisition as the main challenge they face. Metadata completeness and quality are also mentioned as key obstacles. In many cases, metadata are confined by the funding available and the needs of individual researchers to publish their data. This is especially true for NM characterisation, where no publications standards exist, leading to huge discrepancies in reporting. Lack of sufficient metadata inhibits database managers to implement tools that would help enhance, enrich, promote and increase the interoperability and value of the datasets. Based on the survey responses, tools for (meta)data handling, processing, analysis, and semantic annotation are needed. To promote metadata capturing and further exploitation, the community needs to be informed and educated, within clearly defined guidelines, on data quality, interoperability, reusability and their benefits for the wider community and at an individual level.
Consensus is needed on this guidance with the FAIR principles, both scientific and technical, being the best candidates to date to show the way forward. The introduction of FAIR metrics and FAIR scores for individual datasets, as well as relevant databases, is expected to lead to substantial increase in data quality and interoperability. In fact, all database respondents, who did not have an established FAIR data system, were interested to learn more and to implement such a system. To achieve this, a realistic approach for metadata capturing is needed.
• At the other end of the continuum are (meta)data with a high impact on the confidence in the results from the respective bioassay, as they render the experimental outcomes sensitive to high variations (e. g. , packing factor, effective density of agglomerates, agglomerate stability). Therefore, a thorough physicochemical characterisation is essential for these NP properties, and metadata have to include all information needed to facilitate for e. g. , assessment of the in vitro DD or for in vivo-to-in vitro dose bridging studies. The presented (meta)data continuum (Table  4 ) proposes a balanced set of information dataset that are essential for particle agglomeration to be defined. All DD assessment models rely on detailed information on size, size distribution and effective density of primary particles in the relevant medium of the bioassay, as well as of agglomerates and possible changes over time.
Similarly, it is also clear that a formalising metadata goals does avoid premature standardisation of test methods, i. e. , metadata goals permit greater flexibility in medium selection. In conclusion, the questionnaire has been useful for identifying the metadata required for dissolution studies in nanosafety and is a preliminary step in addressing FAIR and FAIRness scores for NM dissolution datasets. The metadata elements for a journal article or database are a controlled vocabulary (terms and definitions); a set of considerations to be addressed in the Materials and Methods section (media, method, competing reactions, and induction times); and interpretive tools (dissolution reaction, measurement unit, model). The literature identified by respondents on separate instances can be found in references  [140] [141] [142] [143] [144] [145] [146] [147] [148] [149] [150].
On the other hand, significant variance of opinion was observed on issues that can be considered more field specific like the experimental media (and the way these should be listed) and the standardised methods and analytical models. These results demonstrate that cross-field data interoperability and reusability is possible when it comes to NM dissolution, with the caveat that further work is needed to bridge the differences between, for example, the nanosafety and nanomedicine communities. Consensus building needs to focus on the way the different experimental parameters, methods and analytical techniques are recorded and presented. This is especially true for the calculation models, as the responses demonstrated that these are still correlated with disciplinary fields. The more formalised and generalised metadata become, the less terms would be needed to explain different phenomena and the more general ontological terms to annotate the datasets to increase their FAIRness could be established, significantly decreasing the workload to achieve the necessary proof of data equivalence and interoperability.
Lack of metadata is also a major reason for the reproducibility crisis  [151, 152] , often caused by insufficient description of experimental details (so called pre-producibility  [153] ). Here, we want to specifically highlight that even if it looks like a technical problem that can be addressed by the FAIR principles with further work  [154] , we are convinced that it cannot be solved by technology alone. Therefore, significant sections of the paper have focussed on the human factor, i. e. , the need to build understanding and commitment of all players involved in the data lifecycle to improve the status quo, and the need to reach community-wide consensus on levels of metadata completeness making the data fit for reuse in broader settings. To achieve this, we must look beyond the original "technical" FAIR principles that are directed towards database owners and introduce key operational steps which data creators can take responsibility for.
The incorporation of all the data and metadata needed to facilitate data re-use at the study design stage will help deciding on the most relevant experiments and identifying potential experimental and computational gaps. It will also speed up method development and customisation by integrating expertise from different fields and enriching empirical datasets with data or predictions from different sources. To be successful, these attempts need to be complemented with the use of tools (ELNs) that capture the related (meta)data during data generation, whether experimental or computational, with minimal, if any, losses resulting in datasets of higher quality. Furthermore, ELNs can assist with the implementation of FAIRness in the science itself. The development and integration in ELN of pre-annotated customised templates assisting with data generation and capture and guiding the user on (meta)data capture, will significantly decrease the workload for all the data roles presented in Tables  1  and 2 , and increase data availability, interoperability, and reusability, especially in a modern computational (i.
Relevant Databases Need to Make Metadata Submission Mandatory and Implement QA Processes Current practices demonstrate that while there is willingness for a wider range of metadata provision and exploitation, these are still limited in many cases. Most current databases do not currently require detailed metadata in terms of experimental protocols, instruments and software used or computational workflows. In fact, one of the most difficult tasks of database managers is the gathering of detailed metadata. QA and QC practices are generally lacking or are left to the data creators and, partly, to curators or managers that may not have the necessary knowledge to evaluate the data being annotated. The lack of standardised protocols and reporting formats is a further burden. There are persistent claims that protocol standardisation, although helpful in terms of regulatory and governance practices, delay scientific progress and lead to constraints on innovation, but these are unfounded.
While both are cross-disciplinary, the data and metadata requirements are totally different. The robustness of calculated data for regulatory purposes are not fit for purpose for the structured, but fluid, nature of the modelling community  [40]. The current publicly available data may be interoperable under a regulatory or scientific context, but require substantial processing to become computationally usable. This means several assumptions on metadata similarity or expansion of the dataset with relevant metadata is needed to identify statistical similarity or significant difference  [124] [125] [126] [127] [128] [129] [130]. As a result, the currently existing databases do not meet the needs of the modelling community, which has led to the emergence of computational databases, allowing capture of computational descriptors and direct application of modelling tools  [157].
One thing to consider, however, is that the metadata needed to allow reuse across disciplinary boundaries is more comprehensive than the "minimum information" approach employed lately, as these are confined to supporting data reuse to address the specific research question for which the data was initially generated  [29]  and focus on identifying the test NM, rather than wider multidisciplinary use. The metadata requirements of the NIKC database, for example, far exceed the minimum required information and are closer to a complete reporting of all possible types of metadata. The question is how consensus can be reached and who can lead these efforts. Ideally, this needs to happen at community level, i. e. , through the EU NanoSafety Cluster, the EU NCI Working Group on Nanoinformatics (as per the current paper) or the EU-U.
We have attempted to include the flavor of this idea in this metadata paper, but perhaps it cannot be stressed enough. What we need to create and adhere to as a community is not a "metadata standard" but guidelines on what is needed and the call for action of the community to move the discussion from the technical aspects (templates in Excel, ISATAB, web interfaces,. ) to a way, how to get all of us in the community to report the needed metadata including everything we and the community think is essential. It is clear that we cannot support every single person individually but if projects decide on their own standards and make these publicly available, then there are ways to get this metadata into databases. In accomplishing all this, an additional requirement should be that we avoid free text fields if they are not absolutely necessary.
A call to action is needed within the nanosafety scientific community for the establishment of best practice and updating of lapsed or generation of missing standards to facilitate the process. This can be achieved through initiatives and close collaboration of the EU NanoSafety Cluster's Working Group F on Data Management, the NCI Working Group on Nanoinformatics and other bodies like the Asian Nano-Forum. We hope that this paper will be the starting point for invigorating further discussion on the implementation of metadata and scientific FAIR principles for nanosafety data and the generation of further collaborative and consensus articles on, e. g. , NM dissolution or the implementation and use of LIMS and ELNs in everyday scientific practice focussing on nanosafety and nanomedicine.
Acknowledgments: Metadata questionnaire: We thank respondents from the 7 databases that provided details of their current and planned metadata activities:  Peter Ritchie  (IOM),  Stacey Harper  (NBI),  Lucian Farcal (ACEnano) ,  Ivan Stambolic  (NanoCommons),  Jaleesia Amos  ( CEINT-NIKC ),  Willie Peijnenburg  ( RIVM-ECOTOX ), and  Tae-Hyun Yoon  ( NanoS2 ). Dissolution case study: We thank the respondents  Tae-Hyun Yoon  ( Hanyang University ),  Greg Goss  ( University of Alberta ),  Vicki Grassian  ( University of California San Diego ),  Zhiyong Zhang  ( Institute of High Energy Physics, CAS ) and  Wendel Wohlleben  (BASF), and note that an additional eight respondents prefer not to have their names published. Members of the  U. S. National Cancer Institute (NCI) National Cancer Informatics Program (NCIP)  Nanotechnology Working Group including  Egon Willighagen  ( Maastricht University, NanoCommons project ),  Mark Wiesner ,  Christine Hendren  and  Jaleesia Amos  ( Duke University ),  Kaiyan Ni  ( University of Chicago ), and the E.
Therefore, the TP profile number 108 is the one we employ to represent the family of TP profiles best fitting the observations and that we thoroughly discuss in the next section. We performed this same analysis again, but considering the profiles of  Cauley et al. (2019)  and  Wyttenbach et al. (2020)  separately. We obtained that the result on the temperature of the upper atmosphere is robust as is does not depend on the chosen dataset, while the result on the shape and position of the temperature inversion depends slightly on the considered dataset, with the profiles obtained by  Cauley et al. (2019)  leading to a steeper temperature inversion located deeper in the atmosphere compared to what we obtained from the analysis of the profiles given by  Wyttenbach et al. (2020). Figure  6  shows the observed Hα and Hβ line profiles in comparison with the synthetic lines obtained employing the TP profiles number 108 (thick red solid line in Fig.
(  8 ) and that three models satisfied the more restrictive conditions set in Eq. (  9 ). However, all these models display an upper atmospheric temperature in excess of 12000 K, which, given the stellar effective temperature, we consider not being realistic for describing the TP profile of KELT-9b. Furthermore, none of these models leads to a better fit to the data with respect to the TP profile number 108 and also have the problem of being shallower and broader than the observations. It is therefore possible that self-consistent models computing the planetary TP structure underestimate atmospheric heating and/or overestimate cooling. García  Muñoz & Schneider (2019)  showed that, because of the shape of the stellar spectral energy distribution and of the large density of excited hydrogen in the planetary atmosphere, heating through absorption of the stellar UV and optical radiation plays an important role.
Acknowledgements. M. E. Y. acknowledges funding from the  ÖAW-Innovationsfonds IF_2017_03. D. S. and M. R. acknowledge the support of the  DFG priority program SPP-1992 "Exploring the Diversity of Extrasolar Planets " ( DFG PR 36 24602/41 ). A. G. S. and L. F. acknowledge financial support from the  Austrian Forschungsförderungsgesellschaft FFG  project  CONTROL P865968. L. M. L. acknowledges the financial support from the  State Agency for Research of the Spanish MCI through the "Center of Excellence Severo Ochoa " award  SEV-2017-0709 , and from the research project  PGC2018-099425-B-I00. A. W. acknowledges the financial support of the  SNSF  by grant number  P400P2_186765. The authors thank the anonymous referee for the insightful comments.
Patient selection All patients who underwent elective RARS for persistent reflux disease under medical treatment or intolerance to medical therapy from January 2005 to October 2017, were retrospectively reviewed from a prospectively collected database from four European Centers. The four Surgical Departments concerned were tertiary centers performing more than 50 gastro-esophageal procedures/year. The two surgical divisions of the University Hospital of Montpellier, as well as the CHL of Luxembourg and the Institut Mutualiste Montsouris in Paris provided the data. Patients who underwent operations in the emergency setting, interventions mixed with bariatric procedures and PARS performed in other surgical departments were excluded from this survey. This study was approved by the Institutional Review Board (IRB, #2018-07-0186) and it was aligned to Helsinky declaration.
Preoperative evaluation and investigations Poor clinical outcome that justified RARS was defined by the recurrence of reflux symptoms (heartburn, regurgitation and/or chest pain) or by the development of dysphagia with or without recurrent hiatal hernia after PARS. All patients undergoing RARS underwent a comprehensive history and physical exam. A detailed assess of previous operations was performed. Barium contrast radiography of the upper gastrointestinal tract and oesophago-gastroscopy were systematically conducted. Esophageal manometry and pH testing were performed as (87%) of patients. Data on demographic features, BMI, ASA, symptoms, type and time of previous operations were collected.
Follow up and data collection Postoperative complications were assessed as well and graded according to Clavien-Dindo classification  [14]. Severe postoperative complications were defined as Clavien-Dindo ≥ 3. Patients were then re-evaluated after one, six and twelve months from RARS. Radiologic (CT-scan) and endoscopic exams were systematically planned during surveillance. WHO quality of life after surgery was assessed. It was defined by scores of six broad domains of quality of life (the physical domain, the psychological one, independence level, social relationships, environment and spirituality/religion/personal beliefs) and was graded on a 1 to 6 scale (1 = very poor, 2 = poor, 3 = neither poor nor good, 4 = good, 5 = very good, 6 = not known)  [13]. Early failure was defined as recurrence of reflux symptoms or the occurrence of grade ≥4 dysphagia one month after surgery.
Statistical analysis All statistical analyses were conducted by the Department of the Statistical Analysis Unit of the University of Montpellier using GraphPad Prism® and R software®. Descriptive data were expressed as the mean ± standard deviation. Categorical variables and proportions were compared using the Chi-squared test or the Fisher exact test. Logistic regression modeling was performed to identify significant variables to predict failure. The univariate analysis was performed using a logistic regression model where the predicted variables were the outcomes of the surgery in terms of persistence of symptoms (symptomatic versus asymptomatic) and the presence of complications. The variables which were found to have a p-value <0. 15 on univariate analysis were further analyzed using a multivariate logistic model.
A more detailed classification considering frequency and severity of symptoms and anatomical features as well may be more accurate to explore the issue. Study included also patients who underwent anti-reflux surgery more than two times. Furthermore, the preoperative assessment of QoL performed by an appropriate questionnaire for this disease (GERD Health-Related Quality of Life score) was not used. Heterogeneity of the approach have to be reported as well. Open approach was preferred in multi-operated patients and when strong adhesions were detected. Control group including patients with GERD recurrence who was not re-operated is lacking. Finally, despite a long study period, the follow up dropout rate was as high as 19%. However, despite several limits, herein, we reported results (following STROCSS Guidelines  [36] ) of a large cohort of patients who underwent repeat anti-reflux surgery from a multi-centre database.
The presence of large-mass resonances in the data collected at the Large Hadron Collider would provide direct evidence of physics beyond the Standard Model. A key challenge in current resonance searches at the LHC is the modelling of signal-background interference effects, which can severely distort the shape of the reconstructed invariant mass distribution relative to the case where there is no interference. Such effects are strongly dependent on the beyond the Standard Model theory that must be considered as unknown if one aims to minimise any theoretical bias on the search results. In this paper, we describe a procedure which employs a physically-motivated, modelindependent template functional form that can be used to model interference effects, both for the characterisation of positive discoveries, and in the presentation of null results.
Preliminary considerations The most straightforward way to present both positive and null search results is that of working in the context of a given BSM theory; an approach of this type is, by construction, a top-down one. While statistically clean, top-down procedures have two main drawbacks. Firstly, they often have to be repeated, even if the datasets are unchanged, whenever a different theoretical model is chosen. Secondly, the details of how BSM theories are treated in such procedures are under the control of the experimental collaborations, which, among other things, renders it difficult for theorists to assess how tweaking different aspects of the models might improve, worsen, or otherwise affect the search results. For these reasons, it is interesting to consider the opposite viewpoint, namely that of a bottom-up approach in which data are manipulated, and the search results presented using the fewest possible number of theoretical assumptions.
Construction of Asimov toys The analytic description of the PM invariant mass distribution, given by the sum of eqs. (4. 6), (4. 8) and (4. 9), is used to construct the Asimov toy histograms that will be used in our tests. Asimov datasets contain no statistical fluctuations  [18] , and are constructed by setting the content of the k th bin equal to the value of the input distribution, evaluated at the central invariant mass value, q k , of that bin. Bin uncertainties are given by: ∆ k = N total A(q k ) bins i A(q i ) bins i A(q i ) N total , (5. 3) where A(q) denotes the generating distribution of the Asimov (in this case, the analytic PM description), and N total is the total number of events assumed for the dataset. The square-rooted contribution arises from regular counting statistics, while the rightmost factor accounts for the fact that bin contents do not correspond to a number of events.