dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS This study was part of HF-M doctoral dissertation at  University of Bordeaux  ( Fernandez-Mena , 2017b). The work was funded by  Bordeaux Sciences Agro (University of Bordeaux)  and  INRA (currently INRAE) ,  Division of Environment and Agronomy. HF-M  received financial support from  Labex COTE  ( University of Bordeaux, France ) and  Agreenium consortium. The data about farming systems were collected thanks to the  French National Research Agency (ANR)  as part of the  Investissements d'avenir program  (reference:  ANR-10-EQPX-17-Center  d'accès sécurisé aux données-CASD).
Methods: The method used was published in an a priori protocol. Searches included peer-reviewed and grey literature published in English and French. Two online databases were searched using English terms and search consistency was assessed with a test list. Supplementary searches were also performed (using search engines, a call for literature and searching relevant reviews). Articles were screened through three stages (titles, abstracts, full-texts). No geographical restrictions were applied. The subject population included all wild species (plants and animals excluding humans) and ecosystems. Exposures comprised all types of man-made sounds in terrestrial and aquatic media, including all contexts and sound origins (spontaneous or recorded sounds, in situ or laboratory studies, etc. ). All relevant outcomes were considered (space use, reproduction, communication, etc.
Review findings: Our main result is a database that includes all retrieved literature on the impacts of anthropogenic noise on species and ecosystems, coded with several markers (sources of noise, species concerned, types of impacts, etc. ). Our search produced more than 29,000 articles and 1794 were selected after the three screening stages (1340 studies (i. e. primary research), 379 reviews, 16 meta-analyses). Some articles (n = 19) are written in French and all others are in English. This database is available as an additional file of this report. It provides an overview of the current state of knowledge. It can be used for primary research by identifying knowledge gaps or in view of further analysis, such as systematic reviews. It can also be helpful for scientists and researchers as well as for practitioners, such as managers of transportation infrastructure.
[31]  on invertebrates, Patricelli and Blickley  [32]  on birds and Popper and Hastings  [33]  on fishes. Other syntheses are more general and resemble somewhat a systematic map, but their strategies seem to be incomplete. For instance, Shannon et al. [34]  performed their literature search on only one database (ISI Web of Science within selected subject areas) and did not include grey literature. As another example, we can cite Rocca et al. in 2016, a meta-analysis that limited its population to birds and amphibians and its outcome to vocalization adjustment  [35]. As a consequence, a more comprehensive map, covering all species and ecosystems, all sources of man-made sounds and all outcomes, and implementing a deeper search strategy (e. g. several databases, grey literature included) is needed to provide a complete overview for policy and practice.
Outcomes All outcomes related to the studied population, including but not restricted to biology/physiology (e. g. heart rate), use of space (e. g. species distribution, individual movements), intra-and interspecific communication (e. g. song frequencies), species reproduction, ecosystem composition (e. g. species richness, abundance) with several species, sources of noise or outcomes). Consequently, we coded the multiple aspects of these articles on one line in the map database.
Comprehensiveness of the search A test list of 65 scientific articles was established (see Additional file 2, section II) to assess the comprehensiveness of the search string. The test list was composed of the three groups listed below. 1. Forty relevant scientific articles identified by the map team prior to the review. 2. Eight key articles identified using three relevant reviews: Brumm, 2010 (two articles)  [40] , Cerema, 2007 (three articles)  [41]  and Dutilleux and Fontaine, 2015 (three articles)  [42]. 3. Seventeen studies not readily accessible or indexed by the most common academic databases, submitted by subject experts contacted prior to the review (29 subject experts were contacted, 7 responded).
Duplicate removal Duplicate removal was carried out throughout the mapping process using Excel (duplicate conditional formatting and visual identification line by line). Duplicates were removed from each corpus (e. g. intra Scopus duplicates) and between bibliographic sources (e. g. duplicates between Scopus and Google Scholar). The selected citation was systematically the one from Web of Science Core Collection because the metadata linked to the citations extracted from this database are more complete compared to the Scopus database and supplementary literature sources (BASE, CORE, Google Scholar, call for literature).
Data-coding strategy All the articles passing the three screening stages were included in the mapping database, apart from those published in 2019 or 2020. This is because some literature searches did not cover 2019 and others covered only a part of it. Consequently, we decided not to include articles published in 2019 (or in 2020) to maintain consistency in the map statistics. Accepted full-texts published in 2019 or 2020 were not coded and were grouped in an additional file for a possible later update of the map. Each article included in the map was coded based on the full-text using keywords and expanded comment fields describing various aspects. The key variables are: Article description: Article characteristics: • Type of population (taxonomic groups). First, we classified the articles according to four taxa: prokaryotes, vertebrates, invertebrates and plants.
2  for more details). Here again, to categorize the exposure (sources of noise) and the outcomes (types of impacts), we used previously published evidence syntheses on noise pollution and biodiversity, in particular the review by Shannon et al. (2016) (see in this publication Table  2 , page 988 on the sources of noise and Table  3 , page 989 on the impacts of noise)  [34]. For studies only: • Country where the study was conducted; • Type of habitat (terrestrial or aquatic); • Study context: in situ (field)/ex situ (laboratory, aquariums, etc. ); • Experimental (causal)/observational (correlative) study; • Origin of noise (artificial, real, recorded). These metadata were coded according to an a priori codebook (see Additional file 6 in Sordello et al. [36] ) that was marginally adjusted. The final version of this codebook is included as a sheet in the provided database file (see below the corresponding Additional file 9).
In a separate sheet, it also contains the list of excluded full-texts and the reason for exclusion. Among the 29,027 articles initially collected, 9482 were deleted because they were duplicates, 14,503 were excluded on titles, 947 on abstracts and 1262 on fulltexts. A total of 1887 articles were definitively selected after the three screening stages. Among them, 1746 were included in the map to be coded (with 48 more articles manually added or coming from specialist websites) and 141 were grouped in a separate additional file because they were published in 2019-2020 (Additional file 8). The systematic-map database contains 1794 relevant articles on the impacts of anthropogenic noises on species and ecosystems (Additional file 9), of which 19 are written in French and 1775 in English.
Article sources The systematic-map database is composed of 1794 articles that come (see Table  4 ): • mainly from bibliographic databases: 65% (48% from WOS CC and 17% from Scopus); • from the bibliography of relevant reviews in a significant proportion: 19%; • from web-based search engines: 12% (in particular 8% from Google Scholar). Articles coming from the call for literature or the specialist websites and manually added articles represent less than 5% of the map. Regarding the efficiency of the searches, the call for literature, CORE search engine and Web of Science CC database stand out as the most relevant sources of bibliography for this map (Table  4 ). For instance, 27% of the literature received from the call was included in the map as was 15% from CORE, however these two sources represent a very small part of the final map (1% and 3%, respectively).
On the contrary, articles collected from Scopus represent 17% of the final map whereas only 3% of the total number of articles collected from this database were actually relevant. Concerning the key reviews from which citations were extracted, some of these reviews proved to be very useful for the map. For instance, 30% of the bibliography (47 articles) from Gomez et al. [55]  were included in the map (see Additional file 3 for the percentage of extracted/included citations for each key review).
Article types and contents Figure  4a  shows the distribution of article types. The systematic-map database is mainly composed of journal articles (1333, which represent more than 74%). The second highest proportions of article types in the map are book chapters and reports that each represent 8% of the map. Figure  4b  shows the distribution of article contents. The systematic-map database is mainly composed of studies (1340, which represent more than 75% of the map), then, reviews (379, 21%) and meta-analyses (16, 1% with one article that is a mixed review/ meta-analysis). Not surprisingly, the majority of studies (1096/1340, 82%) and meta-analyses (13/16, 81%) were published as journal articles. Reviews are more spread over the different types of bibliographic sources even if they are also mainly published as journal articles (186/379, 49%).
In addition, one review on the impact of ship noise on marine mammals includes a systematic literature search  [96]. Two non-systematic reviews can also be cited, one about invertebrates  [97]  and the other about fishes  [98]. Among all these bibliographic syntheses (including those from 2019), we selected those whose literature collection is based on a standardized approach (e. g. search string, database request, screening process)-which includes meta-analyses and systematic reviews/maps or similar-and whose topic is as close as possible to our systematic map (e. g. focused on noise and not on wider human pressures). We summarized the main features (topic delimitation, search strategy, number of citations) for the 12 selected evidence syntheses in Table  6  with more details in Additional file 10.
In most cases, these reviews and meta-analyses contain far fewer articles than what we collected, which can be explained by their topic restrictions (P, E, O) as well as their search strategy (e. g. number of databases, complementary searches or not, screening criteria). In terms of topics, Shannon et al. [34]  would appear to be the only standardized evidence synthesis as wide as ours (all wildlife, all sources of noise, all impacts), but the authors gathered 242 articles from 1990 to 2013. The synthesis published by Radford  [54] -which, as a report, is grey literature-also provides an overview of the state of knowledge with descriptive statistics, according to a standardized method, although it focuses on non-marine organisms and it is based on 86 articles. In 2019, Kunc and Schmidt published a meta-analysis that covers all impacts of noise on animals and they collected 108 articles  [53].
It can be due to practical reasons such as better dissemination and accessibility of articles (e. g. database development), but it also certainly reflects a real increase in research activity on the topic of "noise pollution" in response to social concern for environmental issues. The articles are mainly provided through academic sources (i. e. journal articles), but grey literature is also substantial. 461 articles included in the map (i. e. around a fourth of the map) can be grouped as ''grey literature'' (books and book chapters, reports, theses, conference objects). In particular, 36 theses from all over the world address this issue. Regarding the population, the systematic map confirms that a very broad range of species is the topic of literature on the effects of noise pollution. Indeed, all of the 11 population classes of our coding strategy contain articles.
Ecosystems are a very significant aspect of biodiversity and will be increasingly integrated in public policies and scientific research, notably concerning ecosystem services in the context of global changes  [139, 140]. Reproduction and mobility of species are essential for the sustainability of their population and we already know that noise can impair them  [141, 142]. Concerning the systematic map, at the moment, we are not able to conclude whether this very rich literature provides strong evidence on impacts of anthropogenic noise on animals. Indeed, we do not know if the studies and other articles confirm or invalidate such Table  6  Features of standardized evidence syntheses organized in chronological and alphabetical order MA meta-analysis, SM systematic map, SR systematic review a All types of search limitations: language restrictions (L), only peer-reviewed articles (PR), restriction to some topic areas (T), exportation of first hits only (FH) b All sources in addition to databases: call for literature (C), search engines (SE), bibliography from relevant reviews (RE), personal library (PL) c Scores are given after the screening stages, but further reductions may have occurred in the ongoing process impacts and if the studies are sufficiently robust for that purpose.
However, our database highlights that a majority of studies are experimental field-based studies. This is a very good point in planning further metaanalyses or systematic reviews with the prospect of quantifying the level of impacts because these studies would probably be selected following critical analysis. For future systematic reviews/meta-analyses, we identified that the three outcomes comprising the highest number of experimental studies (which are the type of content that systematic reviews or meta-analyses would use) are: behaviour (453), biophysiology (391), communication  (145). Given the scope of our map resulting in a high number of population (P), exposure (E) and outcome (O) classes, there is a wide range of possible PEO combinations. Therefore, it is difficult to go further in this report in terms of identifying knowledge gaps and clusters and possible specific questions for future systematic reviews.
Search strategy We are aware that two academic databases (WOS CC and Scopus) in our search strategy is a minimum according to the CEE guidelines  [38]. Nevertheless, WOS CC is the most used database in Ecology and Scopus is probably the second. Furthermore, our overall strategy includes eight bibliographic sources (see Table  4 ) and in particular three search engines. In addition, a large number of hits were exported from each of the search engines (e. g. 1000 citations for each search string on Google Scholar instead of the 300 initially expected). We also completed our search strategy with the extraction of all the bibliographic references from 37 relevant reviews. Finally, when a reference was a part of a more comprehensive article (i. e. a meeting abstract inside a proceeding with multiple abstracts), we checked whether other parts of the article could be also interesting for the map (i.
We also asked for the missing full-texts on ResearchGate. A large number of unretrieved full-texts come from the extracted relevant reviews, from Scopus and from Google Scholar (see Additional file 11, Sheet 2 for more details on retrieved/not retrieved full-texts depending on the bibliographic sources). In the end, we could obtain some explanations for a majority of the unretrieved full-texts, i. e. 25 (7%) are available online but behind an embargo, a paywall or another access restriction, 124 (33%) are not accessible to the map team (unpublished thesis or report, unlocatable conference proceedings, only available in a print journal, etc. ), 47 (13%) would be excluded during screening because of their language (according to Scopus information), 19 (5%) were requested on ResearchGate without any response.
Conclusion This systematic map collated and catalogued literature dealing with the impacts of anthropogenic noise on species (excluding humans) and ecosystems. It resulted in a database composed of 1794 articles, including 1340 studies, 379 reviews and 16 meta-analyses published worldwide. Some systematic reviews and meta-analyses have already been published and were collected, however, no systematic map has yet been produced with so few topic restrictions (all wildlife, all sources of noise, all kinds of impacts) and using such a large search strategy (two databases, three search engines, etc. ). This map can be used to inform policy, provide the evidence for systematic reviews and demonstrate where more primary research is needed. It confirms that a broad range of anthropogenic activities can generate noises which may produce highly diverse impacts on a wide array of taxa.
Acknowledgements The map team thanks: Dakis-Yaoba Ouédraogo (MNHN) and Yorick Reyjol (OFB) for providing comments on earlier versions of the manuscript; Marc Morvan, Magali Morvan and Benoît Pichet from the library of the National Museum of natural History for their help during the pdf search; All the institutions that transmitted full-texts to us during the pdf search, namely the library of the "Arts-et-Métiers" (Isabelle FERAL), the library of the "Ecole de Médecine" (Isabelle Beaulande), the library of the "Maison des Sciences de l'Homme" (Amélie Saint-Marc), the library of the "École Polytechnique" (Claire Vandermeersch), the library of "Sorbonne Université" (Isabelle Russo and Peggy Bassié), the library of "Paris 13 Villetaneuse", ZeFactory ARTELIA (Magalie Rambaudi); all the organizations that relayed our call for literature through their websites or mailing lists, namely the "Centre de ressources Trame verte et bleue", the IENE, the ITTECOP; everyone who transmitted literature to us during the call, namely Vital Azambourg (MNHN), Ludivine Boursier (FRB), Fabien Claireau (MNHN), Patricia Detry (CEREMA), Cindy Fournier (MNHN), Philippe Goulletquer (IFREMER), Aurelie Goutte, Anne Guerrero (SNCF Réseau), Eric Guinard (CEREMA), Heinrich Reck, Antonin Le Bougnec (PNR Morbihan), Barbara Livoreil (FRB), Sylvain Moulherat (TerrOïko), Dakis-Yaoba Ouédraogo (MNHN), Marc Thauront (Ecosphère), Dennis Wansink (BUWA); Barbara Livoreil (FRB) for her help with the protocol of this map; Cary Bartsch for his proofreading and corrections concerning the English language.
Type of bibliographic sources Bibliographic sources Exported citations (A) Included articles after screening stages Systematic map (B) 2019-2020 group (C) Total ratio regarding exported citations (B + C)/A (%) Bibliographic databases Web of Science Core 8544 860 (48%) 115 (82%) 11 Collection Scopus Total (7859 a + 685 b ) 12045 (11,186 a + 859 b ) 306 (17%) 20,589 1166 (65%) 18 (13%) 133 (9%) 3 6 Web-based search engines Google Scholar BASE 3403 (3293 a + 110 b ) 600 143 (8%) 25 (1%) 4 (3%) 3 (2%) 4 5 CORE 327 50 (3%) 0 15 TOTAL 4330 218 (12%) 7 (5%) 5 Call for literature 83 21 (1%) 1 (< 1%) 27 Bibliographies of relevant reviews 4025 341 (19%) 0 8 Specialist websites 9 9 (< 1%) 0 100 Other manually included articles 39 39 (2%) 0 100 TOTAL 29,075 1794 141 7.
| Data scoring and statistical analyses Because data were non-normally distributed we used non-parametric statistics. When non-parametric statistics were not available (i. e. , for stepwise regression analyses and moderation analyses), parametric statistics were performed on transformed data using Box-Cox transformations  (Osborne, 2010). In reporting the results, we follow  Wilkinson (1999)  recommendations and report exact p values (unless p <. 001) and effect sizes. We used Firstly, we assessed the suitability of our tasks for the age range studied. In order to do so we present descriptive data (see Table  1 ) for the entire sample but also for age groups (i. e. , 3-5 years old, 6-8 years old, and 9-11 years old), even though age is not treated categorically in this study. Secondly, in order to assess whether performance on tasks changes with children's age we evaluated their correlations with Spearman's rank correlation tests (r s ).
2019 ). However, taking the correct trophic mode into account is still a challenge. Due to the historical bias, most aquatic protists are still by default categorised as either phytoplankton or protozooplankton. Intensive experimental work is required to determine mixotrophy in protists. While, in the past years, quite a few papers were published that contained lists of currently-proven marine mixoplankton  (Faure et al. 2019 , Leles et al. 2017 , Leles et al. 2019) , there is no database available which allows the trophic mode of aquatic protists to be queried. This makes it very time-consuming to take the trophic mode into account for large data-driven approaches on aquatic protist communities. A further complication is added through the frequent taxonomic changes within the protist community which make it difficult to compare literature references.
th This dataset provides information on the trophic mode of aquatic protists and links them to the WoRMS database that keeps track of taxonomic name changes by using a unique species identifier, the AphiaID. By combining information on trophic modes with an already existing and widely-used database such as WoRMS, the authors hope to make data on trophic modes of aquatic protists more accessible in a machine-readable fashion. Thus, the dataset can help facilitate a better understanding of trophic dynamics and the functional role of protist groups within aquatic ecosystems. The trophic mode of the taxa included in this dataset can be accessed via the attributes of the WoRMS taxa search tool (see, for example, http://www. marinespecies. org/aphia. php?p=taxdetails&id=232772#attributes). However, this dataset is only a start.
Project description Title: A dataset on trophic modes of aquatic protists Personnel: Lisa K. Schneider (management, data collection, literature research, tidy data implementation, data concatenation, manuscript preparation), Konstantinos Anestis (data collection, literature research, manuscript contribution), Joost Mansour (literature research, manuscript contribution), Anna A. Anschütz (literature research, manuscript revision), Nathalie Gypens (data collection, expert knowledge, manuscript revision), Per J. Hansen (data collection, expert knowledge, manuscript revision), Uwe John (data collection, expert knowledge, manuscript revision), Kerstin Klemm (data collection, manuscript revision), Jon Lapeya Martin (data collection, manuscript revision), Nikola Medic (literature research, manuscript revision), Fabrice Not (expert knowledge, manuscript revision), Willem Stolte (management, concept development, expert knowledge, manuscript preparation).
Design description: To gather, analyse and disseminate the trophic mode of aquatic protists, a dataset was submitted to the World Register of Marine Species, WoRMS at http://www. marinespecies. org. WoRMS provides "an authoritative and comprehensive list of names of marine organisms, including information on synonymy" (WoRMS Editorial Board 2017) and this list of marine organisms can be augmented with metadata, such as traits, for example, trophic modes. Each organism is labelled with a unique AphiaID with which it is possible to keep track of taxonomic name changes  (Vandepitte et al. 2015). This approach of keeping track of taxonomic name changes allows the database to be accessed and used in different ways, for example, by searching for single organisms or matching a list of taxa. In this dataset, the trophic mode is defined by assigning one of the three different aquatic protist categories (sensu Flynn et al.