dataesr/scientific-paragraphs-categorization huggingface dataset:
So, we had to. the lab is necessarily totally dematerialized. So only that, a basic lab, it gets tubes with erasers and pencils. And we can manage a lab without having a computer system. Here, we had to totally. yes, dematerialize the entire process. " E-PRES has been designed to be directly used by prescribing physicians before MTB using personalized identifiers and codes. This information can be completed later, during and after MTB's discussions. However, handling the software involves additional work for clinicians: they have to get used to its interface and functioning. An important characteristic of E-PRES is that the progression throughout the different prescribing steps is conditioned on the presence of specific digital information, namely patient consent, clinical information and genomic analysis reports.
The digital data management work is thus crucial to allow the progression of the prescription process. Moreover, E-PRES is an addition to and not a replacement for the pre-existing local software specific to each hospital. The medical manager of one of the platforms explains some of the blockages and resistance from clinicians by the "cumbersomeness" of the operations and the work involved in appropriating the software: "For cancer I think, one part that is blocking is the cumbersomeness. That is to say, we had to create an electronic prescription software called [E-PRES]. Well, like any new software, you have to get used to it, and it takes some time to make an electronic prescription. " Interview with Platform A medical director, April 06, 2021. This implementation "cumbersomeness" also stems from the centralizing role of E-PRES, marked by technical difficulties in making the different software programs interoperable.
Indeed, E-PRES has the function of monitoring the entire genomic test process and the correlated gathering of clinical and biological information. However, on the sequencing platform, part of this information is first managed through two other software, one used to monitor the biological sample preparation and the other to help interpreting the sequencing data. On one of the platforms in particular, these two software are not interoperable with E-PRES. Similar technical difficulties exist with local hospital prescription software. In this case, making the different local prescription software interoperable with E-PRES is not considered as an option by the actors. This brings us back to the problems already studied in relation to the implementation of systems which must be made compatible with systems already in place, and for which the work of unifying and upgrading the information takes a great deal of time  (Bowker and Star, 1999; p.
107-108). Indeed, the clinical information of patients, already present in the local prescription software specific to each hospital, must be adapted and re-uploaded in E-PRES by the professionals. This requires, in addition to the appropriation of a new tool, additional time for entering patient information, which is perceived as too great a burden for some of the prescription doctors. For example, a clinician involved in setting up one of the platforms described the discussions she had with the bioinformatics manager responsible for designing the e-prescription software. "In fact, at the beginning, [the bioinformatics manager] wanted the doctor on [E-PRES] to rewrite the entire form. I told him: in fact, we'll have to do the form on [the hospital's software], then we'll have to redo the form on [E-PRES].
On the contrary, E-PRES is designed to ensure that patients' clinical information is entered in a standardized form, according to international HPO (Human Phenotype Ontology) codes developed to categorize disease phenotypes. They can then be manipulated directly by data processing algorithms developed by the bioinformatics platform. "The prescription is really the entry point and we can collect a lot of information and data that are very important. [. ]. On the genome, it's quite brilliant because as soon as I need data of interest that could be useful for sorting efficiently and automatically in [the other software], I just add boxes in [E-PRES] and I ask the clinicians to fill them in. And in that way, I know that I have this data that is well structured in the nomenclature that I want and I reuse it afterwards directly.
From the point of view of the same designers, beyond the quality of the prescriptions for each patient, it is a question of creating a database in which the clinical information can be directly manipulated by the data processing algorithms developed by the bioinformatics platform to handle sequencing data. Yet, as noted by a designer of E-PRES, this touches upon a crucial expertise of clinicians that is central to their diagnostic work and might be difficult to share. "I don't know if I should say this, but [. ] we have a whole area of clinical research that has been built on identifying the causes of genetic anomalies in their patients. So, it's true that we are dispossessing them a little bit. Well, if they have to put all the data in a shared database, there's a little bit of. I don't know if it's dispossession but.
Supporting digitalization: the invisible work of a genomic test prescription Material, organizational and cognitive issues are at the heart of the prescription process and, as we have just seen, the digitalization of this process requires adaptations from the clinicians, centered on the integration of the E-PRES software into their practices. Yet, the appropriation of this software is not limited to the work of clinicians but is accompanied by an intensification of the dirty work  (Hughes, 1997)  carried out by the non-medical staff. Indeed, besides the training sessions implemented by the PFMG to facilitate the clinician's use of E-PRES, they are also supported by new professionals in charge of invisible tasks.
Training and informing on the use of e-prescription In order to support the learning process of E-PRES, the two platforms have set up webinars. The multiplicity and geographical dispersion of clinicians likely to prescribe throughout the country have led to a digital version of these training sessions. Clinicians can therefore follow them at distance and have access to a prescriber's user manual. The objective of these webinars is 2-fold. If the modules aim first at acculturating clinicians to E-PRES, they also condition their access to the latter. For one of the platforms in particular, it is only after following the tutorial and answered two multiple-choice questionnaires that an account can be created for the clinician: "So, they [the physicians] do a little 30-min learning session. And they answer two quizzes.
Once they have answered. So for the moment it's still manual because. [Laughs. ] We receive the answers by email [. ] And once we have the answers, well, if they have more than 60% correct answers, well. On the two MCQs, in general they don't have too many difficulties. So, we ask them. well, we create an account for them. And then they can start their first prescription on the tool. " Interview with the operational manager of platform A, March 10, 2021 However, these distant training are not enough to get prescribers to use the software. Indeed, the implementation of E-PRES requires a succession of very physical meetings between peers to explain what it is and how it works. We find here the presence of "active relays" (Benedetto-Meyer and Boboc, 2019; p. 101) already studied in the world of private enterprise that accompanies digitalization.
The emergence of new prescription support professions based on the clinical research model While the use of HTS technologies by the PFMG is new in the healthcare setting, several hospitals have already integrated inhouse molecular screening programs based on restricted forms of genetic analyses, i. e. , own gene panels, into their clinical routine. Thus, E-PRES is not only an addition to existing softwares, but it also fits into existing genomic medicine practices. In this context, E-PRES participates in the appropriation of new genomic technologies for care, which are supposed to allow a particularly fine analysis of the patient's genome. Moreover, the software centralizes the follow-up of the different steps of the genomic test and is thus supposed to simplify the monitoring of the results.
So, can you modify. ?" Because as a result, it's under the prescription that you have to modify the gender to regenerate the right data. And then, the bio-info will say: "ah well, it's a male and we can see a male, so everything is fine. " Interview with Platform A Lab  Manager, March 30, 2021  This excerpt reveals the decisive role of the "invisible technician" in laboratory work  (Shapin, 1989)  and, more recently, the cognitive work required to update medical databases  (Pontille, 2010). However, faced with the diversification of administrative tasks assigned to clinicians, the digitalization of prescription imposes, alongside laboratory technicians, the arrival of new professionals who support clinicians, thus participating in the process of stratification of the health professionals  (Freidson, 1988).
A prescription assistant told us, "Physicians don't go to [E-PRES] to look up information: where the sample is and so on. It is not at all practical for them". It is therefore a question of doing "what remains to be done"  (Avril and Vacca, 2020; p. 89)  and what the doctors have not done themselves, covering both the failings of other professional groups and those of the software itself, which is supposed to ensure the monitoring and the centralization of data. Prescription assistants are in charge of monitoring and, above all, of registering the e-prescription. They carry out a whole range of invisible tasks, which go beyond the physical framework of their office and which only become visible when they are not carried out, such as reminders of appointments  (Avril and Vacca, 2020)  with the doctors who prescribe for the signing of consent.
Discussion The Plan FGM2025 embodies the centralized vision of the French State in supporting the implementation of HTS technologies in healthcare. To be effective at the entire national scale, this vision a radical increase in the standardization and digitalization of prescriptions. Consequently, E-PRES appears as a central tool in the PFMG2025 large-scale implementation of genomic in healthcare. The software has a decisive organizational role in the design of new care pathways and in the work division between professionals to integrate the HTS genomic technology into their practices. In addition to collecting and digitalizing information, E-PRES help monitoring the care process, linking and guiding each stage of the genomic test. Digitalizing the prescription by means of software should allow any physician to refer a patient and guarantee the principles of equity for patients.
" Thus, far from dematerializing care, E-PRES has largely intensified the "dirty work, " most often assigned to women, who are poorly recognized, in precarious positions (fixed-term contracts, part-time work, etc. ) and often overqualified. This work is also largely invisible because it is integrated, without leaving any Excerpt from the observation notebook of a workday of a prescription assistant in a health care facility in Parisian region, conducted on March ,. Frontiers in Sociology frontiersin. org trace, into the routine usage of the software. Yet, this work is crucial for the proper running of these pathways and particularly for the respect of deadlines. Ensuring that the software procedure are completed is essential if the HTS genomic analyses should improve care for patients who are often in precarious therapeutic situations.
Conclusion This article analyzes how the digitalization of prescribtion and the organization of health professionals associated with precision medicine are transforming medical work. Far from avoiding any human intervention in the process, eprescription requires the use of digital tools whose manipulation relies on learning and adaptation, but also on inputting, translating and sorting information. The automation and ddematerialization brought by software such as E-PRES, also increases the burden of work done by small hands, very largely feminized. Largely made invisible, these tasks could qualify as dirty work. Yet, given the specificities of the clinical context and the operations of translation from paper to digital (or from one software to another) that are required, they should imply a certain form of expertise.
We have described the centrality of small hands in the functioning of E-PRES but many of them do not have a formal nominal authorization to access it. Further, the software does not keep track of the data entry and formatting work and. Consequently, our enquiry did not allow us to observe the expert work of the little hands in the making. To further describe the effects of digitalization on the work of prescription, additional fieldwork with longer observations of the little hands daily work will be required, with more systematic observations of each task carried out, from data entry to bioinformatics, sorting work and monitoring of the prescription process. This would allow a more specific analysis of this prescription work nature, from the diagnostic work to the announcement of the results to the patient.
Increasing production and use of chemicals and awareness of their impact on ecosystems and humans has led to large interest for broadening the knowledge on the chemical status of the environment and human health by suspect and non-target screening (NTS). To facilitate effective implementation of NTS in scientific, commercial and governmental laboratories, as well as acceptance by managers, regulators and risk assessors, more harmonisation in NTS is required. To address this, NORMAN Association members involved in NTS activities have prepared this guidance document, based on the current state of knowledge. The document is intended to provide guidance on performing high quality NTS studies and data interpretation while increasing awareness of the promise but also pitfalls and challenges associated with these techniques.
Guidance is provided for all steps; from sampling and sample preparation to analysis by chromatography (liquid and gas-LC and GC) coupled via various ionisation techniques to high-resolution tandem mass spectrometry (HRMS/MS), through to data evaluation and reporting in the context of NTS. Although most experience within the NORMAN network still involves water analysis of polar compounds using LC-HRMS/MS, other matrices (sediment, soil, biota, dust, air) and instrumentation (GC, ion mobility) are covered, reflecting the rapid development and extension of the field. Due to the ongoing developments, the different questions addressed with NTS and manifold techniques in use, NORMAN members feel that no standard operation process can be provided at this stage. However, appropriate analytical methods, data processing techniques and databases commonly compiled in NTS workflows are introduced, their limitations are discussed and recommendations for different cases are provided.
Purchase or synthesis of standards for full confirmation can be decided subsequently based on the relevance of the identification, e. g. , frequency of detection, potential ecological or toxic effect, or peak intensity. Table  1  includes several examples of applications in the field of environmental monitoring. The sampling, sample preparation, analysis and data evaluation should be tailored according to the study question, as discussed in later sections, which can limit the applicability of retrospective screening in some cases. First studies on the detection of unknown compounds were already reported in the early 1970s, with the introduction of gas chromatography coupled to mass spectrometry with electron ionisation (GC-EI-MS)  [5]. The early harmonisation and reproducible fragmentation by EI led to the inclusion of standard spectra in libraries, such as the National Institute of Standards and Technology (NIST) mass spectral library, which have been used for identification via spectral match since then.
Suspect screening Non-target screening Identifying expected contaminants in the environment for future monitoring Identifying unknown or unexpected contaminants in the environment for future monitoring Obtaining big picture of pollution by monitoring of large numbers of suspects, e. g. , REACH chemicals, NORMAN SusDat Identifying unknown chemicals from spills, specific emission sources and other events, such as stormwater run-off, industry outflow Specific view on substance class related to specific chemistry, origins or usage, e. g. , bisphenols, per-and polyfluorinated compounds, pesticides Identifying causative chemicals for adverse effects observed through bioassays by effect-based tools including effect-directed analysis Retrospective screening of unknown chemicals / masses of interest in stored raw data to determine extent of previous contamination intensity or absence of a molecular ion in approximately 40% of GC-EI-MS spectra  [7].
Tandem mass spectrometry (MS/MS) provides additional fragment information. Today, MS2 libraries have grown, but are not yet comparable to EI spectra libraries due to lower reproducibility and variabilities in fragmentation with different instruments, techniques and energies applied. Given the rapid development and increasing use of NTS approaches, data quality has become an important topic. This includes procedures for quality assurance/ quality control (QA/QC) as well as assessments of what level of data quality is currently achievable  [8]. Several collaborative trials have been organised by the NOR-MAN network  [9, 10] , the US EPA  [11]  and national communities documenting an ongoing need for more harmonisation. Conferences and workshops have been arranged to exchange and evaluate best practice for preparation, acquisition, and data evaluation of samples for HRMS analysis and subsequent suspect and non-target screening workflows.
First drafts of national guidelines for NTS are available in Germany (German Chemical Society) and the Netherlands (Royal Netherlands Standardization Institute), with a specific focus on water monitoring. The NTS community in the US (BP4NTA)  [12]  proposed an NTS study reporting tool for quality assessment of publications in the field  [13]. In response to the increasing interest in NTS from regulators, risk assessors and scientists, and continuous comments on the need for more harmonisation in this field, NORMAN members involved in NTS activities have prepared this guidance document, based on the current state of knowledge. This document is intended to support scientific, commercial and governmental laboratories in conducting high quality NTS studies, and help those using NTS data to evaluate the pitfalls and challenges with these techniques.
The aim is to provide guidance for all steps Fig. 1  Generic workflow of target, library, suspect and non-target screening of mass spectrometric data acquired using non-target methods (Fig. 1 ): from sampling and sample preparation to analysis, through to data acquisition, data evaluation and reporting in the context of NTS analyses. While most experience within the NORMAN Network still involves water analysis using LC-ESI-HRMS/MS, other matrices and instrumentations will also be covered, reflecting the rapid development and extension of the field.
However, this is currently restricted to an acquisition speed of approximately 1 s, leading to a cycle time that prevents coupling with fast chromatographic front-end separation (e. g. , UHPLC). However, Orbitraps still outcompete TOF instrumentation when comparing dynamic range and resolution. Appropriate cycle times for typical LC-or GC-based separations can be reached with Orbitraps, but more data points per chromatographic peak can be acquired with TOF-MS-based detection. Figure  5  shows the required m/z-dependent resolving power to separate isotopologues, e. g. , heavy isotope 37 Cl from 81 Br, or 15 N 2 from 18 O. This figure also includes the m/z-dependent resolving power over m/z 100-1000 for four selected HRMS instruments (ThermoFisher Orbitrap Exploris 480, Agilent 6545 QTOF-MS, Bruker Impact II QTOF-MS and a Waters Xevo G3 QTOF-MS).
Otherwise, it is also possible to alternate within the sequence between positive and negative ionisation modes. However, the mass axis stability needs to be observed carefully. Finally, there are two different modes to save mass spectrometry data, namely, centroid and profile mode. In the case of profile mode, the Gaussian peak distribution of each MS peak is recorded and saved to the data file, whereas for centroid acquisition only the mass spectral peak apex is saved. The corresponding data files differ significantly in terms of size, with profile data files roughly a factor of 10 larger. Since profile data can be converted post-acquisition to centroid but not vice versa, if storage space is not an issue, it is generally recommended to acquire in profile data and perform the conversion afterwards (see Sect.
An overview of columns is given in Table  5. Splitless, programmable temperature vaporisation (PTV), and other non-split injectors are recommended, possibly using large solvent injection techniques to alleviate some problems associated with sample concentration to low volume. For NTS applications, helium is preferred over hydrogen as carrier gas due to the reactive nature of hydrogen. In addition, a linear temperature gradient is recommended to fully benefit from RI database information. Additional complementary techniques are worth considering for NTS studies. Comprehensive two-dimensional gas chromatography (GC × GC) allows dispersion of the sample constituents in two orthogonal dimensions, resulting in exceptional separation power and peak capacity  [171, 172]. This enhances the separation of contaminants and matrix constituents, which is particularly valuable when analysing raw or sparsely purified sample extracts.
Choice of ionisation Electron ionisation (EI) is the most commonly used ionisation technique for GC-MS. It generates reproducible fragmentation patterns at standard conditions, which allows the efficient use of commercial or self-created EI mass spectra libraries. There are large libraries with low resolution EI spectra that can be automatically queried using any vendor or third-party GC-MS software. NIST 2020 alone contains, for example, spectral information on more than 300,000 compounds and RI information on almost 140,000 compounds  [6]. While the "all in one" EIbased fragmentation of the molecule is informative and acts as a fingerprint, it can only be used in workflows if the compound (spectrum) is present in a spectral database, such as NIST. Unknown identification based on low resolution EI-MS spectra is not yet suitable for routine use in NTS workflows  [173].
Unfortunately, high-resolution EI databases are currently limited to a few thousand compounds and, therefore, are likewise currently insufficient for NTS. Moreover, the intensity of the molecular ion measured in EI mode (70 eV) is relatively low, if present at all. About 40% of the compounds in the NIST 08 library have a molecular ion abundance below 5%  [7]. Without the molecular ion, it is challenging to perform a chemical database search to look for potential molecules that match the exact mass of the unknown feature (see Sect. "Glossary and definitions"). Various vacuum soft ionisation techniques (see Fig. 4 ), such as chemical ionisation (CI), field ionisation (FI), photoionisation (PI), low energy EI, and cold-EI  [174, 175] , as well as atmospheric pressure ionisation techniques [APCI, APPI and atmospheric pressure laser ionisation (APLI)] [176] may provide valuable information on the ionised molecule for compounds that do not display a clear molecular ion in EI.