dataesr/scientific-paragraphs-categorization huggingface dataset:
6% of the days, while frequent visitors co-occurred with each other in 30. 1% and rare visitors with other rare visitors only in 2. 1% (Table  2  and Fig. 1 ). For the Italian site (2,414 dyadic combinations) the comparison between locals could not be made, since only one individual was classified as local. However, all other values reflect the same pattern as in the Austrian dataset (Table  2 ). None of the models with possible combinations of the factors sex, breeding status (breeders versus non-breeders) and estimated age at the first observation improved penalized model fit over the null model, as assessed by AIC, indicating that variation in the data cannot be explained by any of these factors  43. Contrary to our expectation, indicators of dominance do not predict how consistently ravens use a site and meet other individuals.
This is particularly true for the Austrian site, for which our dataset corroborates earlier results that were based on a much smaller sample over a shorter time period  27. At the study site in Italy, presence-absence patterns were similar to those in Austria except for the absence of "local" individuals. This difference may be caused by the feeding regimes at the two sites, with zoo animals being fed during a relatively short time in the morning in Austria, whereas vultures were provided with carcasses throughout the day in Italy. In the latter case, ravens can access the food at any time, resulting in a rather low spatio-temporal coordination among individuals. In such a situation, it is hardly possible for human observers to monitor all birds throughout the day. When ravens can exploit a regular food supply only at certain times of the day as at the Austrian study site, the likelihood of fusion events is enhanced and individual birds are easier to spot.
Study area in France (FRA). Up to approximately 200 ravens can be observed at a garbage dump in Saint Flour, a city in the Massif Central in the middle of Southern France (45. 05°N, 3. 10°E). With the same methods as described above we caught non-breeding ravens and outfitted 18 individuals with GPS-loggers, coloured rings and wing tags. While 10 individuals were released at the trapping site, 8 ravens were translocated over distances of up to 240 kilometres as part of management operations aiming to reduce raven abundance in the surroundings of the garbage dump. In the results section we explicitly indicate the translocated individuals; see also Supplementary Table  S2. The data were collected from April 2015 until end of November 2016 with the same sampling interval as described above. Study area in Italy (ITA).
For this dataset we had no information about sex, territoriality (breeder versus non-breeder) or minimum estimated age. Analysis of presence-absence data. We analysed presence-absence data of marked ravens collected on May 2001 and 31st July 2005 at the Italian study site. For all individuals in each dataset we calculated mean, minimum and maximum values for: the number of consecutive days each marked raven was present or absent, the total number of days it was present and the percentage of days present. Note, that for every individual we only refer to the time between marking and their last observation, since afterwards we did not know whether the raven was dead or just left the area. Ravens that were present more than 2/3 of the days were classified as "locals", those individuals present less than 1/3 of the timespan as "rare visitors" and all others as "frequent visitors".
For every dyadic combination we calculated the percentage of days both individuals were present out of all possible days when they could have been present together (i. e. , the overlap of observation days, when both individuals were already marked and before they had been observed for the last time, % co-occurrence). Finally, for data from the Austrian study site we tested whether sex, territoriality (breeders versus non-breeders) or minimum estimated age at the first observation could explain the average number of consecutive days present or absent and the percentage of being present using generalized linear models (error distribution = beta, link = logit). Analysis of GPS data. For the ravens outfitted with GPS loggers (9 in Austria and 18 in France), we measured for each study area the distance between all individuals at every possible time step.
Acknowledgements We are grateful to  Kurt Kotrschal  and the staff of the Konrad- Lorenz Forschungsstelle  for support and providing the infrastructure. We thank the following students for help with marking and collecting the presence data in AUT:  Kristina Beck ,  Anna Braun ,  Dana Graulich ,  Pauliina Järvinen ,  Sabrina Reimann ,  Hailey Scofield ,  Javier Sierro ,  Michaela Spreafico ,  Georgine Szipl  and  Julia Willer. Further , we thank the following people for help with trapping, marking and data collection in ITA:  Mareike Stöwe ,  Michela Prevarin ,  Arduino Candolini ,  Ylenia Cristofoli ,  Bruno Dentesani ; and the  Riserva naturale regionale Lago di Cornino  for cooperation. We also warmly thank  Mr D. Dalle  and all the professionals from the  Office National de la Chasse et de la Faune Sauvage  (Service Départemental  15 ,  Jeanne Duhayer ,  Elodie Petit ,  Kévin Ollivo ,  Quentin Le Bayon ) for their technical support in trapping, tagging, and monitoring common ravens in FRA.
Biases (including those linked to the search itself ) should be minimized and/or highlighted as they may affect the outputs of the synthesis  [7, 11, 21, 36]. Failing to include relevant information in an evidence synthesis could significantly affect and/or bias its findings. This may also happen over time as new results are published (see section about upgrading and amending). In practice, it is unlikely that absolutely all of the relevant literature can be identified during an evidence synthesis search, for several reasons: (1) literature is often searched and examined only in those languages known to the project team; (2) some articles may not be accessible due to restricted access pay walls or confidentiality; (3) others lack abstract or have unhelpful titles, which make them difficult to identify; (4) others may simply not be indexed in a searchable database.
Minimizing bias may require (1) looking for evidence outside traditional academic electronic bibliographic sources (e. g. grey literature); (2) using multiple databases and search tools to reduce the possibility of bias in the retrieved results; and, (3) contacting organisations or individuals who may have relevant material  [2]. Some biases have been listed in Bayliss and Beyer  [2]  and a few of them are reported here to be considered by project teams as appropriate: language bias  [46]  means that studies with significant or 'interesting' results are more likely to be published in the English language and easier to access to than results published in other languages. The impact of this on synthesis outcomes is uncertain (e. g. [25, 37] ) but the way to reduce the bias is to look beyond the English language literature.
Relationship between searching and scoping Searches occur at several points in evidence synthesis. First, an initial scoping search may be conducted when preparing the project. Scoping aims to quickly assess the quantity and type of articles that are relevant to the question. The scoping search is often conducted only using one or two electronic bibliographic databases. The scoping results may help to estimate the quantity and types of articles available, help to plan the human and other resources required (e. g. number of team members, librarians, translators, statisticians, numbers of documents which need to be purchased, processed and extracted), and determine whether the evidence synthesis question should be refined if resources are insufficient. Second, the full search strategy is developed and presented within the evidence synthesis protocol and possibly reviewed by a third party.
Use of multiple languages Identifying which languages are most relevant for the search may depend on the topic of the evidence synthesis. There are two main challenges with languages for an evidence synthesis; translating search terms into various languages to capture as many relevant articles as possible, and then being able to select and use the paper when not written in a language spoken by the project team members. In many electronic bibliographic sources, articles written in languages other than English can be discovered using English search terms. However, a large literature in languages other than English remains to be discovered in national and regional databases, e. g. JICST for Japanese research. Searching is likely to require a range of languages when relevant articles are produced at the national level, as much of it will be published in the official language of the nations  [8].
Reading the articles of the test-list as well as existing relevant reviews often helps to identify search terms describing the population, intervention/exposure, outcome(s), and the context of interest. Synonyms can also be looked for in dictionaries. An advantage of involving librarians in the project team and among the peer-reviewers is that they bring their knowledge of specialist thesauri to the creation of search term lists. For example, for questions in agriculture, CAB Abstracts provides a thesaurus whose terms are added to database records. The thesaurus terms can offer broad or narrow concepts for the search term of interest, and can provide additional ways to capture articles or to discover overlooked words (http://www. cabi. org/cabthesaurus/). As well as database thesauri that offer terms that can be used within individual databases, there are other thesauri that are independent of databases.
Information about access to databases and articles (coverage) can be obtained directly from the project team by sharing knowledge and experience, asking librarians and information experts and, if needed, stakeholders. Peer-review of the evidence synthesis protocol may also provide extra feedback and information regarding the relevance of searching in some other sources. Some databases are open-access, such as Google Scholar, whereas others require subscription such as Agricola (http://agricola. nal. usda. gov/). Therefore, access to electronic bibliographic sources may depend on institutional library subscriptions, and so availability to project teams will vary across organisations. A diverse project team from a range of institutions may therefore be beneficial to ensure adequate breadth of search strategies.
Types of sources We first present bibliographic sources which allow the use of search strings, mostly illustrated from the environmental sciences. An extensive list of searchable databases for the social sciences is available in Kugley et al. [26]. Other sources and methods mentioned below (such as searches on Google) are complementary but cannot be the core strategy of the search process of an evidencesynthesis as they are less reproducible and transparent. Bibliographic sources may vary in the search tools provided by their platforms. Help pages give information on search capabilities and these should be read carefully. Involving librarians who keep up-to-date with developments in information sources and platforms is likely to save considerable time.
Electronic bibliographic sources The platforms which provide access to bibliographic information sources may vary according to: (A) Platform issues • The syntax needed within search strings (see "Building the search string") and the complexity of search strings that they will accept. • Access: not all bibliographic sources are completely accessible. It depends on the subscriptions available to the project team members in their institutions. The Web of Science platform, for example, contains several databases, and it is important to check and document which ones are accessible to the project team via that platform. (B) Database issues.
Publishers' databases The websites of individual commercial publishers may be valuable sources of evidence, since they can also offer access to books, chapters of books, and other material (e. g. datasets). Using their respective search tools and related help pages allows the retrieval of relevant articles based on search terms. For example, Elsevier's ScienceDirect and Wiley Interscience are publishers' platforms that give access to their journals, their tables of contents and (depending on licence) abstracts and the ability to download the article. Web-based search engines Google is one example of a web-based search engine that searches the Internet for content including articles, books, theses, reports and grey literature (see "Addressing the need for grey literature" and "Searching for grey literature").
It also provides its own search tools and help pages. Such resources are typically not transparent (i. e. they order results using an unknown and often changing algorithm,  [14] ) and are restricted in their scope or in the number of results that can be viewed by the user (Google Scholar). Google Scholar has been shown not to be suitable as a standalone resource in systematic reviews but it remains a valuable tool for supplementing bibliographic searches  [6, 19]  and to obtain full-text PDF of articles. BASE Bielefeld academic search engine (https://www. base-search. net) is developed by the University of Bielefeld (Germany) and gives access to a wide range of information, including academic articles, audio files, maps, theses, newspaper articles, and datasets. It lists sources of data and displays detailed search results so that transparent reporting is facilitated  [35].
Choosing bibliographic management software Specific reference management software may be used to extract the results of the search from the bibliographic source onto a computer or in an online dedicated space (e. g. EndNote online). This can assist future removal of duplicates and eligibility screening  [12]. Establishing an efficient workflow to collect, organize, store and share the articles retrieved by the searches should save the project team's time. Common reference management software includes: EndNote and Reference Manager (subscription), or Zotero (open-source) and Mendeley (freeware). The choice of software is likely to be influenced by available resources and the familiarity of the project team with specific software, and may require training. The choice of software should ideally be made at the beginning of the project, during the scoping, and is particularly important if the project team is dispersed across different locations, to ensure that access to references is facilitated at different stages of the work.
The following elements may help when choosing bibliographic management software: • Ease of transferring references between different software packages in case the project team members do not have access to all packages; • Ability to add extra metadata relevant to the evidence synthesis (for instance coding around language, geographical location of results reported in each article) to assist with study identification or grouping for analysis (including bibliometric analysis); • Limitations that may pose a problem (e. g. EndNote online is limited to 10,000 references); • Possibility to retrieve full-texts, automatically or semi-automatically; • Limitations to the number of users of the software; • Remote access to the software and/or results (to share among team members); • Options for storage (e.
Deciding when to stop If time and resources were unlimited, the project team should be able to identify all published articles relevant to the evidence-synthesis question. In the real world this is rarely possible. Deciding when to stop a search should be based on explicit criteria and it should be explained in the protocol or synthesis. Often, reaching the budget limit (in terms of project team time) is the key reason for stopping the search  [41]  but justification for stopping should rely primarily on the acceptability of the performance of the search for the project team. Searching only one database is not considered as adequate  [26]. Observing a high rate of article retrieval for the test-list should not preclude the conduct additional searches in other sources to check whether new relevant papers are identified.
Submitting the search strategy in the protocol for peer-review Publishing the search strategy in the evidence synthesis protocol enables peer reviewers and stakeholders to provide input at an early stage and to detect missing elements (e. g. keywords, databases of important sources of grey literature), highlight possible misunderstandings, question the relevance of some options (scope, dates, variety of outcomes, etc. ), before the final search is conducted. This step aims to ensure that the search will be of the best possible quality and relevance for the future users of the synthesis. If the scope of the search needs to be restrained due to resource limitations, this is presented to the readers before the review is conducted, and should minimize misunderstanding and criticisms when disclosing the results.
In this sense, parentheses as used in search strings function in a similar way to those used in mathematical calculations. For example: (road*OR railway*) AND (killing OR mortality) (for more explanations about OR, see Boolean operators below). • Phrase searching Some database interfaces allow words to be grouped and searched as phrases by using, for example, double quotation marks. For example, "organic farming", "tropical forest". • Lemmatization Lemmatization involves the automated reduction of words to their respective "lemmas" (roots). For example, the lemma for the words "computation" and "computer" is the word "compute". When using defense as a search term, it would also find variants such as defence. Lemmatization can reduce or eliminate the need to use wildcards to retrieve plurals and variant spellings of a word, but it may also retrieve irrelevant variants (e.
Refining the results The finalised search extracts a first pool of articles that is a mixture of relevant and irrelevant articles, because the search, in trying to capture the maximum number of relevant papers, inevitably captures other articles that do not attempt to answer the question. Screening the outputs of the search for eligibility will be done by examining the extracted papers at title, abstract and full-text  [12]. If the volume of search results is too large to process within available resources, the project team may consider using some tools provided by some electronic databases (e. g. Web of Science) to refine the results of the search by categories (e. g. discipline, research areas) in order to discard some irrelevant articles prior to extracting the final pool of articles and thus lower the number of articles to be screened.
Bibliographic tools for grey literature There are some databases or platforms which reference grey literature. INIST (Institute for Scientific and Technical Information, France) holds the European OpenSIGLE resource (opensigle. inist. fr), which provides access to all the SIGLE records (System for Information on Grey Literature), new data added by EAGLE members (the European Association for Grey Literature Exploitation) and information from Greynet. There are also some programs which can help to make web-based searches for grey literature more transparent, a practice that is part of "scraping methods"  [17]. Examples of sources available for grey literature: • BASE (https://www. base-search. net) allows the selection of document types and provides the option to focus on unpublished material.
Websites of organisations and professional networks Many organisations and professional networks make documents freely available through their web pages, and many more contain lists of projects, datasets and references. The list of organisations to be searched is dependent upon both the subject of the evidence synthesis and any regional focus (see examples in  [5, 27, 34, 45] ). Many websites have a search facility but their functionality tends to be quite limited and must be taken into consideration when planning for the time allocated to such task. Examples: • TROPENBOS is a non-governmental agency created in the Netherlands in 1986. It contributes to the establishment of research programmes in tropical forestry and it has its own website with many documents, including proceedings of workshops, books and articles that contain useful datasets and references.
Keeping track of the search strategy and recording results The project team should document its search methodology in order to be transparent and to be able to justify their use of a search term or the choice of resources. Enough detail should be provided to allow the search to be replicated including the name of the database, the interface, the date of the search and the full search with all the search terms, which should be reported exactly as run  [26]. The search history and number of articles retrieved by each search should be recorded in a logbook or using screenshots and may be reported in the final evidence synthesis (e. g. as supplementary material). The number of articles retrieved and screened and discarded should be recorded in a PRISMA diagram and this usually accompanies the reporting of the search and eligibility screening stages within an evidence-synthesis report (for an example of PRISMA see Frampton et al.
biomedcentral. com/submission-guidelines. The project team may report the details of each search string and how it was developed (e. g. [5] ) and whether the strategy has been adjusted to the various databases consulted (e. g. [19, 27] ) or developed in several languages (e. g. [27] ). Limitations of the search should be reported as much as possible, including the range of languages, types of documents, time-period covered by the search, date of the search (e. g. [27, 45] ), and any unexpected difficulty that impacted the search compared to what was described in the protocol (e. g. end of access,  [19] ).
Part 4-updating and amending searches From the moment a search is completed, new articles may be published as research effort is dynamic. Updating or amending a search may be conducted by the same project team that undertook the initial searches, but this is not always the case. Therefore, it is important that the original searches are well documented and, if possible, libraries (e. g. EndNote databases) of retrieved articles are saved (and, if possible, reported or made available) to ensure that new search results can be differentiated from previous ones, as easily as possible. There are two main reasons why a search needs to be changed. The first may occur when the evidence synthesis extends over a long time period (for instance more than 2 years) and the publication rate of relevant documents on the topic is high.
Do you have access to the original search strings, sources, and can you read these files (proper software available)? • Was the original search protocol adequate and appropriate or does it need revising? • Do you know when the initial search took place and which time boundaries were set up at that time? If not, can you contact the authors to get those details? • If relevant, do you have similar details regarding searches in grey literature? • Do you have access to the same sources of documents (e. g. database platforms), including institutional websites, subscriptions? • Will the same languages be used?.
Acknowledgements BL sincerely thanks the co-authors for their involvement in a long endeavour based on voluntary time. It has been a great experience to try to merge different experiences and understanding of the challenges and tools of systematic searches from different disciplines. We thank the Editor and anonymous reviewers for their constructive comments on the submitted manuscript. We thank  Alison Specht  ( CESAB, France ), for her valuable contribution in final editing of English language and improvement of clarity of this article.