dataesr/scientific-paragraphs-categorization huggingface dataset:
Rationale The rationale for developing a new tinnitus-specific case history instrument was the lack of a detailed structured questionnaire for both screening and profiling tinnitus. Such a questionnaire is an important tool for research because it could enable collection of large-scale datasets for characterising tinnitus heterogeneity and tinnitus aetiology. The ESIT-SQ was developed with two main objectives. The first objective was to create a questionnaire that would allow standardised data collection from the entire adult population, tinnitus and non-tinnitus, which are essential for investigating mechanisms associated with tinnitus. Although there are numerous case history questionnaires for tinnitus patients  (Stouffer and Tyler, 1990; Langguth et al. , 2007; Schechter and Henry, 2002) , we are not aware of any that use common questions for both tinnitus and nontinnitus populations.
For example, the TRI database contains data only from a clinical sample of tinnitus patients and therefore the TSCHQ starts from the basis that the respondent has tinnitus. To address this limitation, the ESIT-SQ is structured in a way that it can be answered by anyone, irrespective of whether or not they have tinnitus. The second objective was to create a detailed instrument for profiling the tinnitus population, considering other relevant case history questionnaires and according to the opinion of researchers within the ESIT consortium. Careful consideration was given to potential risk factors for tinnitus (e. g. demographics, lifestyle, and general medical and otological histories) and tinnitus characteristics (e. g. perceptual characteristics, modulating factors and associations with co-existing conditions).
Examples of questions that are important for tinnitus profiling but are not commonly included in history questionnaire are the history of medical treatments that can cause tinnitus (e. g. ear surgery, neurosurgery, or chemotherapy) and the temporal associations between co-existing conditions and tinnitus onset. It would be preferable to collect such medical history information using interview methods. However, selfreported questions, although not ideal, are the only way to provide additional explanatory leverage with large-scale datasets.
Data handling and data quality of the ESIT-SQ implementation in the ESIT database For projects that are part of the ESIT, data collected using the ESIT-SQ are stored in the ESIT database. The first step taken to ensure high-quality data was to implement the user interface using standardised input fields that can be used to assist and restrict user input where reasonable. One example is the use of standardised inputs for integral values that will report ill-formed input to the user automatically. Whenever a participant decides to save their current progress, the data will be validated on the server side and the results will be reported to the user in various ways. For every validation error, the corresponding question will be highlighted and the part that includes the error will be indicated.
The overall state of data entry will be indicated with localised status messages and textual instructions. Within the internal section of the database, the staff can monitor and review data entry and export the data when needed. Authorised staff can configure custom selection criteria depending on analysis or study requirements. For example, the data export can be configured to exclude datasets that are not fully validated, are missing certain items, or meet other criteria for exclusion. All data are stored in a central database that only authorised personal are granted access to. A role management system is used to enforce different levels of data access. Centre Editors can view and edit individual patient datasets of their respective centre and Centre Experts can additionally export data of all the patients of their centre, for data analysis.
Centre Administrators have all rights as the Centre Editors and Centre Experts and can additionally invite or remove staff members. Staff members that need access to the database receive a password protected user account with a role according to their "Need to know". In general, researchers can only see the data of their own centre. The standardised data assessment and storage in the ESIT database allows efficient multi-centre data analysis of the participating partners. Such analyses are only done with anonymised datasets. Multi-centre analyses include only data from centres participating in the respective analysis. The database does not store personal information like names, addresses, phone numbers, e-mail addresses, or IP addresses that can be used to identify a certain participant directly.
There is a unique identifier that can be used to link and combine data from different sources and the staff can assign a custom external identifier to a participant. The systems storing personal information of a certain patient are maintained exclusively within the local centre(s) that need to identify a patient individually. If a participant can be identified individually, e. g. by the value of the external identifier attribute, and requests for their data to be anonymised or deleted according to the rules set by the General Data Protection Regulation (GDPR), the database administrative staff will, in accordance with the patient's centre(s), anonymise or delete the participants data permanently. The ESIT database is physically located at the Institute of Databases and Information Systems (DBIS) at the University of Ulm, Germany.
The paper and pencil versions of the ESIT-SQ in English, Dutch, German, Italian, Polish, Spanish, and Swedish are provided as Supplementary Material B, C, D, E, F, G and H, respectively. The electronic version of the ESIT-SQ is embedded in the ESIT database and is available for anyone that is willing to contribute the acquired data to the ESIT database. Information on how to participate can be found on the homepage of the ESIT database (European School for Interdisciplinary Tinnitus Research, 2018). Having the option of a paper version is important for those people without access to a home computer or a tablet, but the electronic version has a number of advantages, such as including adaptive testing or automated data validation. For example, question B8 (Supplementary Material B) asks participants suffering from other conditions such as pain syndromes, vertigo, or other ear diseases, to assess the temporal relationship between the onset of these conditions and tinnitus.
In the electronic version, adaptive testing allows automatic generation of the relevant items according to preceding responses. This feature improves usability and allows participants to navigate the questionnaire more efficiently. With regard to automated data validation, the participants' input will be validated whenever they save current progress. Participant will be informed about the validation results and asked to provide responses to all mandatory questions. Investigators can monitor the current state of data entry and review a participant's responses from an internal section of the database. In addition, the automatic upload to the database saves staff resources required for transcribing the responses from a paper version to the database, which in turn also decreases the risk of transcription errors.
These and other measures were designed to improve data quality. The ESIT-SQ is a freely available instrument for the research community, but reference should be given to this article when an author publishes data obtained using this questionnaire. Translation of the ESIT-SQ into other languages could be a further useful step to broaden the utility of this participant history questionnaire. Any additional translations and/or any revised versions of ESIT-SQ will be made available on the website of the ESIT project (European School for Interdisciplinary Tinnitus Research, 2017).
, 2015). Second, the need to maintain a relatively short questionnaire required a trade-off against including more questions. Therefore, questions about individual characteristics that cannot be accurately captured by one or a few questions are not included. Such characteristics that have been shown to be associated with tinnitus include history of noise exposure, personality traits, and coping strategies. For these aspects, there are specifically developed questionnaires that can be used alongside the ESIT-SQ. Third, items included in ESIT-SQ are based on clinical expert opinion and available scientific evidence. Nevertheless, not every included variable has been demonstrated to be important for tinnitus profiling. This needs to be investigated by collecting and analysing data using this tool, and underlines the importance of updating questionnaires based on current knowledge.
Conclusions Traditionally, tinnitus subtyping or profiling has been based on clinical experience, and this approach has been useful in developing frameworks to guide tinnitus assessment and management. It is now important, however, to go one step beyond and design projects that take advantage of technological advances. Combining clinical expertise with analysis of big datasets from well-designed, tinnitus-specific databases can help answer long-standing questions about tinnitus, such as which are the most important variables for tinnitus profiling and/or subtyping. The ESIT-SQ aims to contribute to such efforts by enabling standardised multinational collection of tinnitus-relevant data. It was developed to fill the gap of a self-report research tool suitable for both screening for and profiling tinnitus.
Acknowledgments Thanks to  Sana Amanat ,  David Baguley ,  Pim van Dijk , and  Tobias Kleinjung  for providing comments on the initial draft of questions and response options during the ESIT-SQ development. Thanks to  Astrid Meesters  and  Bart Bartogsveld  for contributing to the Dutch translation of  ESIT-SQ. Deborah A. Hall  is a  National Institute for Health Research (NIHR) Senior Investigator. Silvano Gallus  is an  Honorary Associate Professor  at the  University of Nottingham ,  School of Medicine.
Funding This project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  [ Marie Skłodowska-Curie  grant agreement number  722046 ]. Other funding acknowledgments:  CRC  received research funding from  Vetenskapsrådet  and  European Union 's  Horizon 2020 research and innovation programme GENDER-NET co-Plus Fund  [grant number  GNP-182 ], H€ orselforskningsfonden [grant number  503 ],  Decibel Therapeutics Inc , and Svenska L€ akares€ allskapet [grant number  SLS-779681 ]; NT received funding from  Tysta Skolan  [grant number  FB18-0015 ]; JD and TF are funded by  SWOL Limburgs Fonds voor Revalidatie  [grant number  945-07-715 ]; MSe is funded through the  British Tinnitus Association Senior Research Fellow/Head of Research Fellowship ; DJH is funded through the  NIHR Biomedical Research Centre programme  [grant number  BRC-1215-20003 ] but the opinions expressed in this manuscript are not necessarily those of the  NIHR , the  NHS  or the  Department of Health and Social Care.
Model evaluation The evaluation of the ocean estimates (Fig. B1 ) shows a RMSE of 15 to 17 µatm for the three pCO 2 -based flux products over the globe, relative to the pCO 2 observations from the SOCAT v2019 database for the period 1985-2018. The GOBM RMSEs are a factor of 2 to 3 larger and range between 29 and 49 µatm. The RMSEs are generally larger at high latitudes compared to the tropics, for both the flux prod-ucts and the GOBMs. The three flux products have similar RMSEs of around 12 to 14 µatm in the tropics, around 17 to 18 µatm in the north, and 17 to 24 µatm in the south. Note that the flux products are based on the SOCAT v2019 database; hence these are no independent data sets for the evaluation of the flux products. The GOBM RMSEs are more spread across regions, ranging from 21 to 34 µatm in the tropics, 32 to 48 µatm in the north, and 31 to 77 µatm in the south.
Discussion Each year when the global carbon budget is published, each flux component is updated for all previous years to consider corrections that are the result of further scrutiny and verification of the underlying data in the primary input data sets. Annual estimates may improve with improvements in data quality and timeliness (e. g. to eliminate the need for extrapolation of forcing data such as land use). Of the various terms in the   (GtC). All uncertainties are reported as ±1σ. The budget imbalance provides a measure of the discrepancies among the nearly independent estimates. Its uncertainty exceeds ±60 GtC. The method used here does not capture the loss of additional sink capacity from reduced forest cover, which is about 20 GtC for the years 1850-2018 and would exacerbate the budget imbalance (see  Sect.
The limit of the resolution of the carbon budget imbalance is yet unclear but most certainly not yet reached given the possibilities for improvements that lie ahead. The assessment of the GOBMs used for S OCEAN with flux products based on observations highlights substantial discrepancy at mid-latitudes and high latitudes. Given the good data coverage of pCO 2 observations in the Northern Hemisphere  (Bakker et al. , 2016) , this discrepancy points at an underestimation of variability in the GOBMs globally, and consequently the variability in S OCEAN appears to be underestimated. The size of the underestimation of the amplitude of interannual variability (order of 0. 1 GtC yr -1 , A-IAV; see Fig. B1 ) could account for some of the budget imbalance, but not all. Increasing model resolution or using model ensembles  (Li and Ilyina, 2018)  has been suggested as a way to increase model variability (Sect.
Conclusions The estimation of global CO 2 emissions and sinks is a major effort by the carbon cycle research community that requires a careful compilation and synthesis of measurements, statistical estimates, and model results. The delivery of an annual carbon budget serves two purposes. First, there is a large demand for up-to-date information on the state of the anthropogenic perturbation of the climate system and its underpinning causes. A broad stakeholder community relies on the data sets associated with the annual carbon budget including scientists, policymakers, businesses, journalists, and nongovernmental organisations engaged in adapting to and mitigating human-driven climate change. Second, over the last decade we have seen unprecedented changes in the human and biophysical environments (e.
Helena anticyclone (e. g. ,  Klein and Hartmann, 1993; Pfeifroth et al. , 2012). So far, the relative roles of these different processes in the frontogenesis of the ABFZ still need to be investigated. In this study, following the fundamental philosophy of GC2014, we attempt to understand the mechanisms responsible for the climatological ABFZ development at a seasonal timescale based on a first-order estimation. We propose an ocean frontogenetic function (OFGF) in a different way from GC2014 focusing on the OML mean front. The structure of the remainder of this paper is as follows. Sect. 2 gives details of dataset used in this study. In Sect. 3, we derive the OFGF. Section 4 provides a description of the climatological state around the ABFZ. In Sect. 5, we apply our diagnostic methodology to the ABFZ and determine the main terms of the frontogenetic function controlling its annual mean and seasonal cycle.
Acknowledgements. We greatly appreciate two anonymous reviewers for their constructive and helpful comments. Also, we would like to express our appreciation to  Kunihiro Aoki  in the  University of Tokyo  for his constructive discussion in the initial stage of this study. We also thank  Guy Caniaux in Météo-France  for their helpful discussions. We used the 2012Rb versions of the MATLAB software package provided by  MathWorks, Inc. , (http://www. mathworks. com,last access:  13 August 2018 ) and  Grid Analysis  and Display System (GrADS, http://cola. gmu. edu/grads/, last access: 30 November 2018) to compute each dataset and create figures. Shunya Koseki  has received funding from the  EU   FP7/2007-2013  under grant agreement no. 603521  ( EU-PREFACE ) and STERCP ( ERC , grant no. 648982 ).
Data availability. The CFSR reanalysis data  (Saha et al. , 2010)  used in this study can be downloaded from https://climatedataguide. ucar. edu/climate-data/climate-forecast-system-reanalysis-cfsr. The data of OISST  (Reynolds, et al. , 2007)  are available at https://www. ncdc. noaa. gov/oisst. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/os-15-83-2019-supplement.
To complete this catalogue, a decision table has been designed to select potential tsunamigenic events within the USGS earthquake database, using criteria on the distance to New Caledonia, the magnitude and the hypocenter depth. Then a crosscomparison between these earthquakes, the NOAA National Geophysical Data Center (NGDC) tsunami catalogue and local tide gauge records provided 25 events that were recorded in New Caledonia for the period from 30 September 2009 to 10 January 2019. These events are added to the 12 events reported with certainty during previous studies, leading to a number of 37 tsunamis triggered by earthquakes reported or recorded in New Caledonia since 1875. Six of them have been identified only thanks to local tide gauges, supporting the fact that instrumental recording of tsunamis is paramount for tsunami hazard studies, from early warning to the valida-tion of coastal models.
Methodology This study is based on the USGS earthquake catalogue that provides accurate information on seismic events that have occurred all around the world since 1 January 1900 (US Geological Survey, 2019). A decision table has been created to select the events within this database that were potentially tsunamigenic and had potential to reach the New Caledonia coastlines. The events extracted are then cross-compared to the tsunamis reported from the NOAA National Geophysical Data Center (NGDC) tsunami database and the NOAA Pacific Tsunami Warning Center (PTWC) bulletin archives and to local marigraphic data.
Data selection with magnitude criteria The first step was to collect all the available earthquakes from the catalogue for the Pacific Ocean region. We decided to select only the M w > 6. 3 events according to global tsunami databases, like the Historical Tsunami Database for the World Ocean (HTDB/WLD; http://tsun. sscc. ru/tsunami-database/index. php, last access: 21 January 2019) or the NOAA NGDC/WDS Global Historical Tsunami Database (https://www. ngdc. noaa. gov/hazard/tsu_ db. shtml, last access: 24 August 2018), which empirically show that there is no tsunami triggered by earthquakes of magnitude M w < 6. 3  (Tinti, 1991). Further,  Bolt et al. (1975)  indicate that the maximum run-up for a tsunami generated by a M w = 6. 5 earthquake would be no more than 0. 5-0. 75 m, and  Walker (2005)  shows that tsunamigenic earthquakes with moment magnitudes M w ≥ 8.
Relationship between earthquake magnitude and focal depth and tsunami generation We use the data from the NOAA NGDC/WDS Global Historical Tsunami Database to plot the earthquake focal depth as a function of magnitude for 440 tsunamigenic earthquakes that occurred around the world from 1 January 1970 to 24 August 2018 (Fig. 2 ). Only 47 (10. 7 %) of these events have M w < 6. 3, and 9 (2. 0 %) have been located at a depth of more than 100 km. Considering that these events are not located within the Pacific Ocean, and/or they did not produce a sufficient tsunami to be recorded in New Caledonia, we decided to only look at earthquakes of magnitude M w > 6. 3 and fo-cal depth < 100 km in the following. Note that these values are consistent with different early warning systems' criteria  (Tinti, 1991 ; UNESCO/IOC, 2009).
2 ) within the framework of the ReefTEMPS project  (Varillon et al. , 2018)  or the EMIL project  (Aucan et al. , 2017b). Their characteristics are also summarized in Table  1. Tide gauge and pressure data were detided by removing the predicted tide. The predicted tide was calculated with a harmonic analysis of the entire dataset available for each site, all of which were longer than 6 months.
Tsunami catalogue The decision table has been able to extract 967 events (M w ≥ 6. 3) from the USGS earthquake catalogue that occurred between 1 January 1900 and 10 January 2019. At first we decided to look only at the events that occurred after the period considered by  Sahal et al. (2010) , i. e. , after the 29 September 2009 Samoa tsunami. This represents 113 from the 967 extracted events. But not all these events triggered a tsunami and even fewer a tsunami able to reach New Caledonia. To look at their tsunamigenic capa-bilities, this list of earthquakes was cross-compared with the NOAA NGDC/WDS Global Historical Tsunami Database, which provided 44 events that were reported as tsunamigenic (last download date: 24 August 2018). This list includes events like the 27 February 2010 Chile M w = 8.
8 or the 11 March 2011 Japan M w = 9. 1 earthquakes. The 44 tsunamigenic events represents 38. 94 % of the 113 events extracted from the USGS EQ database. For the period from 24 August 2018 to 10 January 2019, nine events were extracted from the USGS database with the decision table. Amongst them, only two were followed by a NOAA PTWC bulletin indicating they triggered a tsunami. Thus, there are 46 (44 + 2) tsunamigenic events for the period from 29 September 2009 to 17 January 2019, corresponding to 40. 71 % of the 113 identified earthquakes. From these 46 events, only 14 were followed by a tsunami recorded in New Caledonia according to the observations included within PTWC bulletins. An in-depth look at the other 32 events (46 -14) case by case has been performed to identify small tsunamis that could have been missed by PTWC analysis (i.
b. Looking at tide gauge data From September 2009 to February 2011 only the Nouméa tide gauge (Numbo) operated at high enough frequency to record any potential tsunamis. Although eight extracted tsunamigenic earthquakes were reported by PTWC bulletins during this period, none were recorded by the Numbo tide gauge, even the M w = 8. 8 earthquake of 27 February 2010 that occurred in Biobio, Chile, recorded on nearby islands (Tonga, New Zealand, Australia, French Polynesia, etc. ). For the period from February 2011 to January 2019, there are still 24 (32 -8) tsunamigenic events extracted from the list. Hienghène and Ouinné tide gauges have been chosen to iden- tify the corresponding recorded signals since these two tide gauges located on the east coast of the Grande Terre (Fig. 5 ) are exposed to several tsunami sources and are located in bays or estuaries that could amplify tsunami signals.
Events before 29 September 2009 For the period before 29 September 2009,  Sahal et al. (2010)  collected 18 events, including 12 events related with certainty to an identified earthquake. These 12 events are detailed in Table  3. There is a strong uncertainty in the accuracy of the 6 other reported events concerning the date as well as the source. Eleven out of the 12 seismic events reported by  Sahal et al. (2010)  and shown in Table  3  have been kept with the decision table; the first one from 1875 is beyond the range of the USGS database beginning on 1 January 1900. These 11 events are part of the 854 extracted events by the decision table for the period from 1 January 1900 to 29  September 2009 (inclusive). This represents less than 1. 29 % of earthquakes of magnitude M w ≥ 6. 3 being able to produce a tsunami reaching New Caledonia over this period.