dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We thank  Anne Harzen  for support in the MS experiments. We thank  René Richter ,  Franziska Turck , and  John Chandler  for critical comments to the article. This work was supported by the  European Molecular Biology Organization  ( AFL-2017-74  to A. P. ), the  China Scholarship Council  ( 201804910196  to X. Y. ), the  Deutsche Forschungsgemeinschaft under Germanys Excellence Strategy  ( DFG EXC 2048/1  Project ID:  390686111  to G. C. ), and is supported by a core grant from the  Max Planck Society.
Data, materials, questionnaires, and pictures of the intervention's setting can be found here: https://osf. io/9gbst/. Since our experimental design does not allow us to isolate the causal factors that contributed to change people's minds, we will not speculate on the role that might have played the exposition to the scientific consensus (Gateway Belief Model) or argumentation. But from our data we will be able to infer: (i) whether participants changed their minds, and (ii) if, on the contrary, cases of backfire were common. Based on the literature reviewed above, we predict that our intervention will change people's minds in the direction of the scientific consensus (H1) and that cases of backfire will be rare (H2).
Results and discussion All statistical analyses in this paper were conducted in R (v. 3. 6. 0, R Core Team, 2017), using R  Studio (v. 1. 1. 419, RStudio Team, 2015). Since pre-and post-intervention responses were anonymous and could not be matched, we used a non-parametric test (permutation with "lmPerm" package  (Wheeler & Torchiano, 2016) ) to compare pre-and post-intervention ratings. The permutation test generated all the possible pairings between the pre-and post-intervention ratings of our data set and recomputed the test statistic for the rearranged variables (for a detailed explanation see: Giles,.
Acknowledgements We would like to thank  Hugo Mercier  and  Camille Williams  for their valuable feedback and numerous corrections on previous versions of the manuscript. We are also grateful to all the participants with whom we had great discussions and who took the time to fil in our boring questionnaires. We thank the organizers of the science festivals, Cognivence,  Starsbourg University  and  Vanessa Flament , without whom nothing would have been possible. We also thank  Joffrey Fuhrer  who animated the workshop with us for one afternoon. Lastly, we are grateful to the two anonymous referees for their valuable feedback.
astro. uni-jena. de/Laboratory/OCDB/amsilicates. html (OCDB database). The extinction efficiency Q ext was computed at 0. 55 and 1. 65 µm wavelengths. In the Mie approximation, the extinction efficiency can be translated to an opacity via the equation: κ = 3Q ext 4aρ , ( 8 ) where a is the radius of the dust sphere and ρ is the density, all in CGS units. The typical density of 3 g. cm -  from the OCDB database was used. The opacities were computed for radii ranging from 0. 5 nm to 100 µm to explore the different regimes of the Mie scattering. The plots of Fig  7  show the opacities for the two species of dust as a function of radius at 0. 55 and 1. 65 µm as well as the κ V /κ H ratio. The opacities are quite similar for the two species of dust except for radii below 0. 01 µm. The AAVSO data of Fig  5  show that the two V-band maxima before and after the median date of the observation (JD2453654) are brighter, respectively, by a 0.
With these assumptions, the maximum global flux attenuation can be computed as a function of the strength parameter a in Eq. 1. The maximum attenuation is 5% with the Gaussian model, whereas it reaches 10% with the exponential model. In consequence, we used the exponential model to explore the variations of the attenuation and of the m. κ V product versus a. The maximum for the geometrical characteristics of the patch derived in the H band is an attenuation of 10% of the flux corresponding to a difference in magnitude of ∆V = 0. 11. This is compatible with the maximum brightness decrease with respect to the two neighboring V-band maxima. This cannot, however, be the only source of the dimming in V as the AAVSO data show cycle-to-cycle variations up to a magnitude or more. Unless several such patches are episodically produced.
Acknowledgements. This research has made use of  NASA's Astrophysics Data System Bibliographic Services , the SIMBAD and AFOEV databases, operated at  CDS, Strasbourg, France  and of the AAVSO database. The work of  STR  is supported by  NOIRLab , which is managed by the  Association of Universities for Research in Astronomy (AURA)  under a cooperative agreement with the  National Science Foundation. We thank the anonymous referee for suggestions which improved the content and presentation of the report.
The proposed schema consists of the following four steps: (i) Front-loading phenomenology: Formulate hypotheses about the subjective features of the target psychological phenomenon; (ii) Online second-personal interview: Conduct a face-to-face interview to participants who are undergoing the psychological phenomenon in question in order to collect descriptions of its subjective features; (iii) Questionnaire survey: Obtain responses to a questionnaire designed to test said hypotheses from the participants; (iv) Hypothesis-testing: Evaluate said hypotheses based on the data acquired through the second and third steps. A distinctive feature of our experimental schema is that it creatively incorporates the method of phenomenal contrast. Some philosophers have suggested that disputes about subjective features, which cannot be settled in terms of direct introspection of the psychological phenomenon at issue, may be resolved by comparing it with similar phenomena  (Kriegel 2007; Siegel 2007).
Online second-personal interview In recent consciousness studies, second-personal interview has often been employed to elicit rich and reliable phenomenological reports from experimental participants who do not have relevant background knowledge  (Petitmengin et al. 2007; Valenzuela Moguillansky et al. 2013; Høffding and Martiny 2016). We also adopted the second-personal interview to obtain descriptive data about BR-and FBR-experience. While there have been a few attempts to ask experimental participants to describe their experiences of BR  (Cosmelli and Thompson 2007; Knapen et al. 2011) , there is no attempt to conduct a systematic online second-personal interview for studying the subjective aspect of BR. The interview consisted of three steps. During the whole interview, the participants were free to request the experimenter to present them with either the BR or FBR stimulus.
Questionnaire survey A questionnaire survey was also conducted to collect quantitative data about the subjective features of BR and FBR. The participants could not see each stimulus when answering the questionnaire. The participants filled in the questionnaire by writing. Except for the question 3, it used a scale of agreement from -3 to 3 (a seven-point Likert scale), which consisted of "strongly disagree" (-3), "disagree" (-2), "weakly disagree" (-1), "no opinion" (0), "weakly agree" (1), "agree" (2), and "strongly agree" (3). The questionnaire consisted of 25 questions (Table  1 ). Three questions of them (1-3) were designed to evaluate the difficulty of the discrimination task. The third question about the accuracy rate includes the options of 0-15%, 15-30% and 30-45% to cover the cases where participants consistently mistook BR for FBR in the discrimination task but noticed at some later point of the experiment that they made such mistakes.
In this stage, each meaning-unit was evaluated in regard to whether it supports/conflicts with each working hypothesis. The fourth stage is to produce a general structural description of the experience. The orthodox approach is to generate structural accounts of the experience in question for each participant's descriptive data and then to compare them to arrive at the most general structural account. In the current experiment, however, this last step was not taken because the purpose of the qualitative data analysis was not to develop a new account of the general structure of BR-experience, but rather to test the working hypotheses about it already generated through the front-loading method. One final adaptation was that while Giorgi's method is typically conducted by an individual analyst, we performed the analysis collectively.
Discussion The objective of this study was to introduce and justify CEP as a new experimental phenomenological method to investigate the subjective features of psychological phenomena. CEP proceeds in the following four steps: (i) Front-loading phenomenology (Working hypothesis section), (ii) Online second-personal interview (Online second-personal interview section), (iii) Questionnaire survey (Questionnaire survey section), and (iv) Hypothesis-testing (Hypotheses testing section). CEP employs phenomenal contrast in the experimental design, which distinguishes it from other experimental phenomenological methods, such as microphenomenology and experience sampling methods. We tested the validity and productivity of CEP by applying it to study the subjective features of BR. We first constructed eight hypotheses about the subjective features of BR and then tested them against two sets of phenomenological data obtained through online second-personal interview and questionnaire survey.
Strengths and limitations of this study ► Very few studies highlighted the clinical pharmacists' key role for optimising therapeutic management in lung transplant outpatients. ► A strength of this study is the assessment of pharmacist's clinical impact through a new validated scale and the analysis according to the Pareto principle. ► Another strength is that pharmacist's added value is underlined through a collaborative practice model in lung transplantation over a 7-year period. ► The main limitation was the retrospective assessment of clinical impact in a single-centre study. ► Another limitation was not to be able to follow patients longitudinally through the anonymised database. Open access and the impact of clinical pharmacists' interventions (PIs) is poorly studied in lung transplantation as only one study in Canada with a small sample size was reported.
Study design and population A retrospective observational study was performed on the PIs recorded on Act-IP website observatory from 1 January 2009 to 31 December 2015 and related to the 152 LT recipients followed at the 2200-bed Grenoble University Hospital over the 7-year period. Patients were eligible if they were lung transplanted before 1 January 2009 or between 1 January 2009 and 31 December 2015 according to our computerised hospital register of transplantation. All patients gave written informed consent to use their data for research.
PIs data and Act-IP database After registration on the Act-IP website, pharmacists can record and analyse their interventions. Entering an intervention in the database took 15 min on average. The type of DRP and PI was classified according to the SFPC criteria using the report forms developed and validated for routine documentation. 22 The pharmacist prospectively completed the anonymised online report form specifying the date, pharmacist rank (senior or resident), patient demographic characteristics (age, sex), drug(s) involved in the DRP coded according to the Anatomical Therapeutic Chemical classification,  23  DRP description, PI description and acceptance or not by the physician. Physician's acceptance was defined as prescription modification or change in medical care or therapeutic management.
Potential significance of PIs The impact of accepted PIs recorded on Act-IP database was assessed according to an SFPC validated tool adapted for the French clinical practice named CLEO. This tool includes a clinical dimension with several numeric levels including negative, null and positive impacts (Minor, Moderate, Major, Avoids fatality), and an open level 'undetermined', which evaluates patient's benefit according to the most likely case expected if no PI is performed  19 24  on April 13, 2022 by guest. Protected by copyright. http://bmjopen. bmj. com/ BMJ Open: first published as 10. 1136/bmjopen-2020-041563 on 27 November 2020. Downloaded from Open access (an additional file shows this in more detail (see online supplemental appendix 1)). Clinical assessment was performed by an independent expert committee (a pharmacovigilance expert, a pulmonologist and a clinical pharmacist) from Grenoble University Hospital during a face-to-face meeting.
After the presentation by the meeting moderator of each accepted intervention, each expert independently and blindly evaluated the clinical impact of each of these interventions prior to discussion to reach an expert consensus from available data: age, gender, patient's history, a description of the DRP and the PI according to the classification of the SFPC, drug(s) involved and clinical and biological information. No inter-rater agreement was measured as each PI was rated after expert consensus. In order to guarantee the quality of the interventions recording on Act-IP database, data management was performed by a pharmacist resident before expert assessment.
Statistical analysis PI was the unit of analysis. Data were described as mean and SD for quantitative variables, and frequency and percentage for qualitative variables. PI description included all data and the clinical impact was assessed for accepted PI because of change in patient management from pharmacist's evaluation. The clinical impact of PI was presented using bar charts, a matrix assessing the relationship between it and DRP, and a Pareto chart. The Pareto chart using 'ABC analysis' is a useful tool for analysing what problems need attention first and is based on the 'Pareto principle', a theory maintaining that 80% of the output in a given situation or system is produced by 20% of the input (group A). The other inputs are categorised in group B (15% of the output) and group C (the last 5% of the output).
Open access PIs were mostly related to 'untreated indication' (n=42) and 'subtherapeutic dosage' (n=38) but the reason of non-acceptance was not explained in Act-IP database. However, we can hypothesise that the reasons of nonacceptance may be related to stable patient condition without any adverse event or pharmacist's lack of information at the time of analysis. Our study highlights the added value of clinical pharmacist in lung transplantation as clinical impact of accepted PIs was positive in 98. 9% of cases and none had negative clinical impact. PIs allowed stopping major or lethal clinical outcomes in 7. 1% of cases. DRPs to be detected as a priority were wrong dosage and untreated indication problems, associated with a moderate clinical impact in almost 70% of cases. The clinical impact was more important for subtherapeutic dosage problem than for supratherapeutic dosage problem, according to the risk of graft rejection.
Clinical pharmacists should be aware of drug-drug interactions as they were related to moderate or major clinical impact in more than 80% of cases. The Pareto chart revealed that immunosuppressants, antimycotics for systemic use and antithrombotic agents were the most implied drug classes in PIs with major or lethal clinical impact which require pharmacists' attention: clinical pharmacists took proactive steps with the transplant team to resolve these problems and developed or optimised protocols such as azole initiation monitoring recommendations. A double quality control process was performed to guarantee data reliability. PIs' impact was assessed by consensus of a multidisciplinary expert committee, including a pulmonologist. Only accepted PIs were evaluated because they represented the real impact of the pharmacist in LT outpatients' management.
Some limitations have to be underlined. All the DRPs may be not detected by clinical pharmacists, because of pharmacist residents' lack of experience or pharmacist's lack of time. Indeed, each pharmacist resident is trained by a senior pharmacist at the beginning of his internship but without reaching senior's experience level, that is why the pharmacist controlled all recommendations to make sure they were optimised. In addition, not all identified DRPs may be recorded on the Act-IP database although it was mandatory, which may lead to an underestimate of DRPs prevalence. This possible under-reporting could not be excluded, particularly for non-accepted PIs. Our data could not be presented in terms of patient proportion as all the PIs were recorded anonymously in the Act-IP database. We acknowledge that there was no control group in this study.
Introduction There is a paucity of data that can be used to guide the management of critically ill patients with COVID-19. In response, a research and data-sharing collaborative-The COVID-19 Critical Care Consortium-has been assembled to harness the cumulative experience of intensive care units (ICUs) worldwide. The resulting observational study provides a platform to rapidly disseminate detailed data and insights crucial to improving outcomes. Methods and analysis This is an international, multicentre, observational study of patients with confirmed or suspected SARS-CoV-2 infection admitted to ICUs. This is an evolving, open-ended study that commenced on 1 January 2020 and currently includes >350 sites in over 48 countries. The study enrols patients at the time of ICU admission and follows them to the time of death, hospital discharge or 28 days post-ICU admission, whichever occurs last.
Data collection Data collection methods Streamlined data collection instruments and procedures are used to minimise the workload at study centres. Data  ). Figure  1  outlines the schedule of assessments used for patients included in the COVID-19 CCC study. De-identified study data are collected and managed using the REDCap electronic data capture tool hosted at the University of Oxford, UK. 16  Data will not be used for any purpose other than those described in the study protocol. Each site's principal investigator is responsible for ensuring data integrity. Regular written and web-based training is provided. In countries unable to upload data into a centralised database, the ability to retain a local database on a national server is available, with aggregated anonymised data exported centrally for analysis.
Patients will not be enrolled under the conditions of an amended protocol, until after approval has been granted. It is expected that this study will not require informed consent in most jurisdictions. This study is, in effect, a large-scale clinical audit, as all data are collected routinely. This may justify a waiver of consent. Any jurisdiction that deems informed consent necessary may use forms provided on our websites (https://www. elso. org/ COVID19/ ECMOCARD. aspx). Within such jurisdictions, patients who meet the eligibility criteria will be approached directly. If this is not possible, due to the patient's incapacity, a model of retrospective or representative consent may be used, per local requirements.
Background: Adherence to chronic therapies is crucial to prevent the progression of disease, such as glaucoma. However, only a limited number of studies have investigated them using real-world data in Japan. This study aimed to evaluate Japanese patients' adherence to fixed-and unfixed-combination eye drops as a second-line therapy for glaucoma in real-world practice. Methods: This retrospective, non-interventional cohort study utilized a commercially available Japanese healthcare database (MinaCare database). Medical/pharmacy claims data were collected from 2011 to 2016. The primary endpoint was adherence to medications, assessed by proportion of days covered (PDC) with medication during a 12-month post-index period. Meanwhile, the secondary endpoints included the persistence rate. Results: A total of 738 patients were included in this study: 309 and 329 in the fixed-and unfixed-combination cohorts, respectively.
Risk factors for nonadherence to glaucoma therapies include patients' problems (financial concern, poor understanding of the disease, and frequent eye drop application), healthcare providers' issues (insufficient instruction/explanation and assessment of each patient's conditions), and the relationship between patients and physicians (lack of communication and trust)  [12] [13] [14]. A previous study reported that a fixed-combination therapy improved the long-term adherence of patients with glaucoma compared with the unfixed therapy  [15]. According to a nationwide survey performed in 2011-2012 in Japan using a questionnaire, good adherence to IOPlowering eye drops was observed in 72. 4% of patients  [16]. However, these risk factors and adherence rates were based on the data obtained from clinical studies under controlled conditions or an experimental setting.
Therefore, patients' adherence to the therapies should be investigated, and the risk factors in ordinary clinical settings should be determined using real-world data. In several previous studies, adherence to glaucoma therapies was evaluated using pharmacy claims data  [17] [18] [19] [20] [21] [22]. Unfortunately, to our knowledge, no such study has been conducted in Japan. Therefore, this study aimed to compare patients' adherence between a fixedcombination therapy and an unfixed-combination therapy and to identify risk factors for nonadherence in Japanese patients with glaucoma by using a healthcare database.
Study design This retrospective cohort study utilized a commercially available Japanese administrative healthcare database (MinaCare Co. , Ltd. , Tokyo, Japan) to investigate the adherence of patients to fixed-combination and unfixedcombination therapies for glaucoma treatment after switching from a monotherapy. The study consisted of a 12-month pre-index period, an index date (defined as a first prescription day of either when a single eye drop was first switched to a fixed-combination therapy [fixedcombination cohort] or when the second eye drop was added to a single eye drop initially [unfixed-combination cohort]), and a 12-month post-index period. Patients without claims for 12 months after the index date and those who claimed the third drug in addition to a fixedcombination therapy or in addition to an unfixedcombination therapy indicated withdrawal.
Data source and study cohort The MinaCare database includes anonymized data on both health checkup and medical/pharmacy claims of workers and their family members in a wide range of age groups below the age of 75 years  [24, 25]. Maintained by MinaCare Co. , Ltd. , this database is updated periodically with newly available data obtained from the employment-based health insurance groups. It includes the data of 6. 3 million uniquely identified individuals as of April 2017 and has recorded the information of 1. 8 million patients from April 2016 to March 2017, covering 1. 7% of the Japanese population under the age of 75 years  [26]. Furthermore, it is generally consistent with two national databases and is useful as it has low selection bias and large sample size with wide age distribution; however, it only targets national-wide big corporations, such as manufacturing, food, information transportation, and energy industries, and does not include individuals in the primary industry (agriculture, fisheries, forestry, etc.