dataesr/scientific-paragraphs-categorization huggingface dataset:
Participants Among the 35 persons contacted, 25 (71. 4%) were enrolled in this study. Specifically, 5 (14. 3%) did not meet the study inclusion criteria and 5 (14. 3%) did not agree to participate. Recruitment of the study participants was conducted in April 2017 in two sites (Turin and Rome) and the data collection was performed in the period of May/June 2017. Participants satisfying all of the following criteria were included: i) they were aged over 65 years; ii) they agreed to test a connected device and to wear it continuously on 7-day duration; iii) they were able to come to the test centre by themselves or accompanied by a family member; iv) they were able to understand and answer the study questionnaires; v) they could walk independently with or without the use of assistive devices.
Statistical analysis Descriptive analyses were carried out for all the study variables. Based on the data provided by ADAMO, the following three continuous variables were obtained and used for statistical analyses: In other words, the first two levels consisted of lying, sitting or performing light activities activities, while the other level consisted of walking activities at usual or sustained pace. For each individual, the sum of Low, Moderate and Vigorous Activities variables returns a score of 100%. Firstly, controlling for age and gender, one-way analysis of covariance (ANCOVA) was performed to investigate differences in Low, Moderate, and Vigorous Activities between frail and robust individuals. Secondly, cluster analysis was carried out to detect participants with similar levels of Low, Moderate and Vigorous Activities.
Specifically, the following two steps was performed: (i) hierarchical cluster procedure using Ward's method to individuate the appropriate number of clusters by observing the dendrogram; (ii) k-means clustering to partition individuals into k homogenous groups. Using one-way analysis of variance significant differences across the cluster centers were identified. Lastly, to test the association of clusters based on the MI levels and the 400 m walk test with frailty total, physical, psychological, and social frailtylinear regression analysis, controlling for participants' age and gender, was carried out. The Statistical Package for Social Sciences, version 24. 0 (SPSS Inc. , Chicago, IL, USA) was used for the analyses. The level of significance was set at p < 0. 05.
Acknowledgements The authors would like to thank  Samuel D'Emanuele  and  Denis Giacone  of  University of Torino (Turin, Italy ) and  Valeria Galfano ,  Alice Tassi  and  Kseniya Tretyakova  of  Sapienza University (Rome, Italy ) who collaborated in the recruitment of participants and in the data collection. A special thanks is for the older adults who took part in the study.
Sample Online samples of approximately 1000 adults from the German general population were recruited both for Germany 1 and 2 surveys. The survey was sent out as a weblink for the respondents to complete at their leisure. Potential respondents are members of an online panel of persons willing to complete surveys for small payment. Participants were eligible if aged 18 to 80 years. Representativeness of the sample was investigated by comparison with national census data  [22]. As the age and sex distribution in the Germany 1 sample differed considerably from that in the general population, quota sampling by age and sex was used in the Germany 2 valuation to achieve representativeness for these variables. Additional sources had to be accessed to obtain estimates the population prevalence of chronic diseases in persons aged 18-80, as no differentiation within the group of persons aged 65+ was made in the official statistics.
Modifications of DCE analysis and additional analyses (i) Some of the utility decrements obtained in the analysis did not show a monotonic pattern, i. e. , increasing severity coinciding with increasing decrements. When this occurred, the non-monotonic levels were combined. This restriction has been standardly imposed in previous studies  [4, 10, 25]. (ii) As the distribution of age and gender in the Germany 1 valuation sample differed significantly from the German population, a weighted analysis was performed in addition to the unweighted one. For this, the sample was stratified by age group and sex, imposing weights to achieve representativeness for each combination of the two variables  [19]. (iii) Additional analyses of the DCE data were performed by means of mixed logits, for both the Germany 1 and 2 datasets.
Complete cases and dropouts An overview of the respondent flow is given in Appendix (Table  5 ). A proportion of those invited to the survey dropped out immediately, upon reading the description of the survey (14. 3% and 10. 0% for Germany 1 and 2, respectively); presumably it did not interest them. Further, for the Germany 2 survey, 34. 4% were excluded as they were excess to quota sampling for their age and sex; there were no such exclusions for Germany 1, as there was no quota sampling. Of the remainder, completion rates were close to 90%. Specifically, 1002 of 1135 (88. 3%) respondents entering the Germany 1 valuation component of the survey and 1016 of 1124 (90. 4%) respondents meeting the quota-sampling criteria for the Germany 2 valuation completed all the survey components. These 'complete case' respondents form the analysis dataset for all results reported below.
b The key secondary endpoint was the composite of cardiovascular death, myocardial infarction or stroke. due to synergistic mechanisms of action (statin-ezetimibe combination therapy) but also reduce levels of other molecules involved in hypercholesterolaemia (statin-fibrate combinations in lowering TG)  [1, 2, 19, 23]. Following the observed decrease in CV events in patients with type 2 diabetes and low HDL-C and elevated TG levels (a prespecified subgroup with atherogenic dyslipidaemia) with fenofibrate-simvastatin combination therapy in the ACCORD Lipid trial  [25] , the PROMINENT study (NCT03071692, https://clinicaltrials. gov) is currently evaluating a new selective peroxisome proliferator-activated receptor alpha modulator, pemafibrate, in addition to statin therapy. Additional benefits of combination therapy include increased adherence  [27] , which is a key strategy in increasing therapeutic efficacy  [1].
This led to the constitution of a HTA consultative committee with stakeholders involved in the LBP health care pathway (eg, health care professionals, patients, managers, HTA experts). The hospital-based HTA unit was in charge of animating this committee. In doing so, the hospital-based HTA unit performed three systematic reviews. The first was on the safety and efficacy of corticosteroid injections, with or without anesthetic, for various types of chronic LBP. The second was about the other treatments currently recommended for chronic LBP by clinical practice guidelines. The third was about patients' preferences for factors underlying the choice of non-surgical treatment. The unit also conducted a survey on the health care services currently offered in our region and collected data about patients' preferences.
Literature review A systematic literature search has been conducted up to June 2018 in PubMed, Sciencedirect and Scopus. The objective of the literature review was to identify which attributes and levels were already reported in the literature as being important to patients. This would serve to answer the DCE aim to identify which attributes are important to LBP patients in their decision to choose a non-surgical treatment. The methodology of this systematic review is comprehensively described elsewhere. 23 In brief, two reviewers independently selected the articles according to inclusion and exclusion criteria, one reviewer then extracted the data while the other verified and completed it when necessary. Any disagreements were arbitrated by a third reviewer. The quality of each included study was evaluated by each reviewer using the Mixed Methods Appraisal Tool (MMAT).
Acknowledgments: Calculations were performed on the AUGURY supercomputer at P2CHPD Lyon. We thank  F. Dubuffet  for help on the supercomputer. We thank  M. Tetley  and  A. Holt  who helped us improve the English writing. Funding: The support for this research was provided by the  European Union 's  Horizon 2020 research and innovation program  under  ERC  grant agreement no. 617588. Author contributions: All authors contributed to the development and analysis of the models, preparation of the figures, and writing of the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The code StagYY is the property of  P. J. Tackley  and  ETH-Zürich  and is available for collaborative studies from  P. J. Tackley  (paul. tackley@erdw.
Data The dataset was based on the merging of several sources. First, purchases were computed from scanner data from the 2010 Kantar Worldpanel. This survey registers households' food purchases, i. e. , quantities and expenditure. Households with complete purchase data were selected resulting in a sample of 7,134 households. Environmental data were collected using Greenext, an environment consultancy that assessed the environmental impact of 311 food products in France based on life-cycle analysis  (Goedkoop et al. , 2009). The final values were represented by three different indicators: GHG emissions (gCO2eq/100 g), air acidification (gSO2eq/100 g), and marine water eutrophication (gNeq/100 g) denoted as CO2, SO2 and N, respectively. These estimations are the only ones available in France for food environmental impact.
This work has been partially supported by  INRA DIDIT Metaprogramme  and the  French National Research Agency  in the framework of the " Investissements d'avenir" program  (IDEX  Univ. Grenoble Alpes, IRS). None of these sources had any involvement in any stage of this research. This work was supported by the  INRA DIDIT Metaprogramme and IDEX Univ Grenoble Alpes. None of these sources were involved during any stage of this research.
Data source This was a cross-sectional study using secondary data from routine records. The setting and district monitoring system have been previously described  6. In the current study, however, all public health facilities in the Western-Area District, Sierra Leone, were included: 110 PHUs, 9 secondary and 4 tertiary hospitals. The study population included all people reported with cardiovascular disease (CVD), HTN, DM, mental health disorder (MHD) and tumours/cancer in June-December 2013, June-December 2014 and June-December 2015. Data sources were the aggregate monthly NCD reports available at the Directorate of Policy, Planning and Information, Ministry of Health and Sanitation.
Acknowledgements This research was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership coordinated by the  Special Programme for Research and Training in Tropical Diseases at the World Health Organization (WHO/TDR ) and implemented with partners. The training model is based on a course developed jointly by the  International Union Against Tuberculosis and Lung Disease  ( The Union ) and Medécins sans Frontières (MSF). The specific SORT IT programme which resulted in this publication was jointly developed and implemented by:  WHO/TDR , the  Sierra Leone Ministry of Health ,  WHO Sierra Leone, the Centre for Operational Research, The Union, Paris, France; the Alliance for Public Health, Ukraine; the Institute of Tropical Medicine, Antwerp, Belgium ; and  Sustainable Health Systems, Freetown ,  Sierra Leone.
Funding: This research was conducted with the support of the Research Initiative "Modélisation des marchés actions, obligations et dérivés" financed by HSBC France under the aegis of the Europlace Institute of Finance. The views and opinions expressed in this presentation are those of the author alone and do not necessarily reflect the views or policies of HSBC Investment Bank, its subsidiaries or affiliates. The PhD thesis of Marc Chataigner is co-funded by a public grant as part of investissement d'avenir project, reference ANR-11-LABX-0056-LLH LabEx LMH.
Research in context Evidence before this study Evidence of the impact of cash transfers on tuberculosis outcomes is highly variable. We searched the Cochrane Library for relevant articles published from database inception to April 30, 2016, using the search terms "cash transfer" and "tuberculosis treatment". We considered studies if they investigated material incentives in patients with active or latent tuberculosis. A Cochrane review showed that, at present, insufficient evidence exists to conclude that cash transfers can improve long-term adherence to tuberculosis treatment. However, studies in Ecuador, Moldova, and Peru suggest higher rates of cure among people who were beneficiaries of cash transfers than those who were not. In Brazil, the national conditional cash transfer scheme, the Bolsa Familia Programme (BFP), provides income assistance for impoverished households on the condition that beneficiaries participate in pro-health and educational activities.
BFP has been associated with improved health outcomes, including nutrition, childhood mortality, and antenatal care for recipients, but the effect of this intervention on tuberculosis outcomes remains unclear. Retrospective secondary data from Brazil have shown the potential rate of cure among BFP beneficiaries during tuberculosis treatment was 7% higher than that of patients not exposed to BFP, with no improvement in other tuberculosis outcomes. These previous analyses were dependent on datasets with few variables available to control confounders, limiting their ability to assess causal associations between cash transfers and tuberculosis outcomes.
Study design and participants We did a prospective cohort study of individuals who had initiated treatment for tuberculosis at 42 healthcare centres in seven cities (Manaus, Fortaleza, Recife, Salvador, Vitoria, Sao Paulo, and Porto Alegre) in Brazil between March 1, 2014, and April 30, 2017. The seven cities were selected because they had the highest incidence of tuberculosis nationally in 2012, and are highly repre sentative of all administrative regions in Brazil, with regard to the socioeconomic and demo graphic compo sition of the population. Healthcare centres were included if they had a treatment success rate for tuberculosis that was less than the WHO target of 85%, at least 20 individuals were diagnosed with tuberculosis at the centre in the year before data collection, and tuberculosis was treated in accordance with the National Tuberculosis Program of the Brazilian Ministry of Health recommendations.
Procedures All participants were prospectively followed up for the entire tuberculosis treatment course. Trained healthcare workers did surveys and health assessments at enrol ment, and during the second and sixth month of tuberculosis treatment, with the exception of Salvador, where data collection was coordinated by a team from the Federal University of Bahia (Salvador, Brazil). Information about individual characteristics (sex, age, ethnicity), socio eco nomic status (years of education, occupational status, monthly income, household goods), living conditions (sewerage system, waste collection, housing conditions), current lifestyle (smoking status, alcohol use, and illicit drug use), comorbidities (eg, HIV or AIDS, diabetes, kidney disease), anthropometric data, allergies, presence of bacillus CalmetteGuérin scar, previous history of tuberculosis (date of diagnosis, disease type, pharma ceutical regimen, results of exam ination during treatment, adverse drug reactions, response to directly observed therapy), and coverage of health insurance and receipt of social benefit (type, values) was recorded.
Statistical analysis We required a sample size of 1200 to detect a difference in treatment outcomes of 10% between individuals that received cash transfers from the BFP (BFP group) and those that did not receive BFP (nonBFP) with 86% power with 5% significance (appendix). In our study database, tuberculosis treatment outcome as a variable had the highest frequency of missing data (14%). The mean proportion of missing data for other variables was 5%. We imputed missing data using the missForest algorithm. Random forest is an ensemble learning method that combines the predictions from multiple decision trees to produce more accurate predictions. 23 We used MICE random forest with 1000 trees. The imputation analysis was done using the R Project program (version 3. 3. 3). Categorical variables including sex, ethnicity, years of education, occupation, sewerage system, waste collection, lifestyle, HIV or AIDS, comorbidities, and health insurance were presented as absolute and relative frequencies (%).
The model is calibrated based on estimated parameters for the euro area, using monthly data over 1999-M09 to 2007-M12. While using standard definitions for variables in the model, a key issue is how to measure financial imbalances (the bubble). We use the MSCI (Morgan Stanley Capital International) index, which is an aggregate index measuring equity valuations. The deviations from fundamental values are assessed based on the Arbitrage Pricing Model (APM), where actual equity prices are compared with their "fair values". Fair values of equity are estimated based on the presumption that equity price variations are affected by surprises due to shocks on various fundamental variables (See Appendix 1 for further details). A second set of parameters from  Smets (2000)  and corresponding to annual data for the euro area, are used for simulating the model and check the robustness of our findings.
The measurement metric used was the annual number of publications of various types that either endorsed the existence of global warming, or rejected it, or expressed no view either way. Figure  7  shows a view of the Cook data in a way that resembles the plots in Fig. 1. The plots should be interpreted as: 'With a long period to achieve a nominal 25 year target, few papers were published. Nearer the target the number of publications increases'. Both plots show a gradual drift to consensus (that global warming is a significant problem) that fits the PA mode. Consumer and business confidence Confidence in the economy can be measured by two OECD indices: the consumer confidence index (CCI) and the business confidence index (BCI). The CCI is based on the monthly OECD Consumer Confidence Survey of 5000 households.
Mexico is a good example of a middle-income country with a large informal sector. In our representative dataset, one third of all workers are informal and frequently transit in and out of formal jobs. About 20 percent of informal employees transit to a formal job within a year and about 10 percent of formal employees transit to an informal job within a year. We develop and estimate a search and matching model where formal and informal jobs arise endogenously and where transitions between formality regimes occur both between and within jobs. Firms face monetary penalties for hiring informally. Workers and employers search for potential partners to enter a job relationship. When they meet, they observe the value of the match-specific productivity that contributes to the overall output of the match, together with the workers' human capital.
Firms optimally post the formality status for each specific match and wages are determined by bargaining. At a given point in time, each worker can be in one of four possible labor market states: formal employee, informal employee, self-employed, and unemployed. The human capital evolution while participating in the labor market captures the additional productivity that may be acquired on the job. We allow this dynamic to depend on the formality status of a job. While off-the-job and searching (either as unemployed or as self-employed), individuals may even lose previously accumulated knowledge, leading to a depreciation of human capital. We estimate the model using longitudinal data from Mexico's official labor force survey, the Encuesta Nacional de Ocupación y Empleo (ENOE). There are two main sources of variations in the data for the identification of the parameters governing the human capital dynamics:  (i)  transitions between jobs and labor market states; and (ii) wage growth within and between jobs, conditional on formality status.
Data The data is extracted from Mexico's official labor force survey, the Encuesta Nacional de Ocupación y Empleo (ENOE). Similar to the US Current Population Survey, the dataset has a panel component -households stay in the sample for five consecutive quarters. We stack together two cohorts of individuals entering in the first quarter of the year 2013 and in the first quarter of 2014, respectively. This information, combined with quarterly panel data on wages and labor market status, allows us to fully characterize the labor market trajectories for the individuals in our sample (job-tojob transitions, wage growth within and between job spells, as well as changes in the formality status within the same job). Section A of the Web Appendix provides further details about the construction of the longitudinal sample employed in the analysis.
We define the unemployed as those who declare: (i) not to be working during the last week; and (ii) actively searching for a job. Earning distributions are trimmed at the top and bottom 1 percent in each labor market state (formal employees, informal employees and self-employed). The final sample used in our empirical analysis is a balanced panel dataset comprised of 4,936 individuals observed every quarter for five quarters, either starting in the first quarter of 2013 or in the first quarter of 2014. Table  1  and Figure  1  depict the main cross-sectional facts; Table  2  reports statistics on labor market dynamics. The observed patterns are broadly consistent with previous evidence for Mexico and with aggregate evidence from Latin America. First, there is a significant mass of workers in each labor market state: about 60 percent of workers are employed formally and 35 percent informally.
In Section B. 3 of the Web Appendix, we provide additional details on how we implement the truncation and discretization of this distribution in the simulations used in estimation. The discretization of the continuous exponential draws is needed because we have assumed a discrete grid for the support {a k } K k=1. In the case of the human capital downgrading shock, we dispose of more limited information since -as common in most standard labor market datasets -we do not observe much about the searching process. Specifically, we observe durations and transitions over the searching states but we do not observe either the number or the amount of offers actually received. The downgrading 22 The unknown parameters in the most flexible specification are (K-1) because -as shown in the second row -τ f,K is zero by definition (no additional upgrading can take place when reaching the upper bound of the human capital distribution).
To describe the wage dynamic, we consider the wage growth on the job and across jobs one year apart, taking into account if there is an episode of search longer or shorter than a quarter when changing job. We compute average wage growth both on the overall sample and by quintiles. The final estimators include 62 moments and 18 parameters. To assess the reliability of our estimator, we perform a Monte Carlo procedure in which the point estimates obtained by applying our estimation procedure on the original data are compared to the point estimates obtained by applying the same estimation procedure on synthetic data generated by known parameters. We find them close enough to lend credibility to our estimation method. Details and results on the Monte Carlo procedure are reported in Section C. 1 of the Web Appendix.