dataesr/scientific-paragraphs-categorization huggingface dataset:
This issue highlights the need for careful curation of voucher specimens and associated data with databased molecular sequences; without this information it is difficult for users of barcoding databases to confirm and correct erroneous reference sequences  (Vilgalys, 2003). Vouchers allow matching of tissues and sequences to actual specimens, a critical factor for the validity and repeatability of taxonomic studies  (Agerer et al. , 2000; Cerutti-Pereyra et al. , 2012). Not all species are barcoded and available for comparison, as is the case with our putative sample of the Scoophead Shark, S. media. In addition, the quality and length of sequences cataloged on online databases is variable, and there are only partial sequences for some species. These limitations make it challenging for this study and others to catalog the diversity of life using barcoding methods.
2; S1 -Available only as online supplementary file accessed with the online version of the article at http://www. scielo. br/ni). Hammerhead diversity included four species: Scalloped Hammerhead Sharks [Sphyrna lewini (Griffith & Smith, 1834)], Great Hammerhead Sharks [S. mokarran (Rüppell, 1837)], Golden or Smalleye Hammerhead Sharks [S. tudes (Valenciennes, 1822)], and Bonnethead Sharks [S. tiburo(Linnaeus, 1758)]. We also provide photographic evidence for the presence of S. media Springer, 1940, the Scoophead Shark, although since sequence data for this shark is not available in either BOLD or BLAST databases, we cannot yet confirm its presence in Guyana waters with DNA barcoding. Carcharhinid diversity numbered nine species, with the most abundant being.
Acknowledgments The authors thank  C. Osborne  and  D. Hemraj  for their assistance in the field. The authors are also indebted to  World Wildlife Fund Guianas  for providing the opportunity and funding for this project, particularly  C. Hutchinson  and  A. Williams. We thank two anonymous reviewers for their feedback, and thank  C. Chabot  for advice on early drafts of this manuscript. Without funding from the  Rufford Foundation  to M. A. K. and E. L. , the pilot information for this project would not have been possible. M. A. K. was funded by an  Ontario Provincial Trillium  fellowship and A. E. , M. A. K. , and N. R. L. were supported by the  National Sciences and Engineering Research Council of Canada funding. D. Taphorn  has been instrumental in organizing the cataloguing of ichthyofaunal diversity in the Guianas and the authors are indebted to his mentorship and tireless energy.
2; S1 -Available only as online supplementary file accessed with the online version of the article at http://www. scielo. br/ni). Hammerhead diversity included four species: Scalloped Hammerhead Sharks [Sphyrna lewini (Griffith & Smith, 1834)], Great Hammerhead Sharks [S. mokarran (Rüppell, 1837)], Golden or Smalleye Hammerhead Sharks [S. tudes (Valenciennes, 1822)], and Bonnethead Sharks [S. tiburo(Linnaeus, 1758)]. We also provide photographic evidence for the presence of S. media Springer, 1940, the Scoophead Shark, although since sequence data for this shark is not available in either BOLD or BLAST databases, we cannot yet confirm its presence in Guyana waters with DNA barcoding. Carcharhinid diversity numbered nine species, with the most abundant being Sharpnose Sharks [Rhizoprionodon lalandii (Valenciennes, 1839) and R.
Approach The overall aim of this research was to describe the characteristics of questionnaires used to assess barriers of clinical guideline use among physicians, rather than evaluating or summarizing the survey outcomes or barriers identified; therefore, a scoping review approach was used. A scoping review can be used to describe the quantity and quality of research in a given area and identify gaps that can be addressed through ongoing research  [12]. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria guided reporting of the methods and findings  [13]. Data were publicly available so institutional review board approval was not necessary. A protocol for this review was not registered.
Searching MEDLINE and EMBASE were searched in March 2015 for studies published from January 1, 2005 to December 31, 2014 that reported the results of a questionnaire administered to assess barriers of guide use among physicians. The search was updated in July 2016 to include studies published from January 1, 2015 to that date. These databases were chosen because they are the most extensive sources of peer-reviewed medical literature. The chosen time span coincided with the publication of the Baker et al. systematic review on tailoring, first published in 2005, then updated in 2010 and 2015 with similar findings  [9]. The search strategy was purposefully broad to enhance sensitivity (Additional File 1 at www. jclinepi. com). The search strategy was comprised of Medical Subject Headings only that matched the concepts of guideline use and barriers.
As search results were reviewed, selection criteria were expanded to specify studies that were not eligible. Studies were not eligible if they focused on barriers of guideline use in general; guidelines focused on logistical procedures (eg, informed consent, sign-out, referral); were directed at patients, health professionals other than practicing physicians, or single respondents representing organizations; the study design was based on qualitative interviews rather than a questionnaire; or if they were publications in the form of guidelines, conference proceedings or abstracts, protocols, letters, editorials, or commentaries. A data extraction form was developed to collect information on author, publication year, country, clinical topic, clinical intervention, setting of respondents, specialty of respondents, mode of questionnaire administration, type of response options, any underlying theory explicitly named in the methods that informed questions, validation of the questionnaire (pilot-testing, psychometric testing), and barriers addressed by the questionnaire.
Data analysis Clinical topic or intervention addressed by each questionnaire was coded as a disease category using the International Classification of Diseases-10 (ICD-10), version 2015 (apps. who. int/classifications/icd10/). Summary statistics were used to describe the number of studies by year published, country, clinical topic and intervention, disease category, setting and type of respondents, mode of questionnaire administration, response options, underlying theory, validation, and barrier domains based on the Flottorp et al. framework  [8]. The quality of individual studies was not assessed because that is not customary for a scoping review.
However, the Flottorp et al. framework may not necessarily be ideal because it relied on published studies and was not based on an overall theoretical standpoint. Several additional issues may limit the interpretation and use of these findings. Although we searched the two most relevant databases of medical literature pertaining to physicians and used rigorous searching and screening processes, our search strategy may not have identified all relevant studies. We did not search the gray literature, assuming that most empirical research on guideline implementation would be found in indexed databases. Publication bias, or the tendency for journals to publish positive results or surveys with high response rates, may have influenced the number and type of studies that were retrieved. We purposefully did not include questionnaires that elicited views about guidelines in general because we were interested in the process of identifying barriers of disease-specific guideline use.
Acknowledgments Members of the  Guidelines International Network Implementation Working Group  (g-i-n. net/working-groups/implementation) reviewed this article to further refine the interpretation of findings and enhance communication of the findings. They included the following: (1)  Melissa Armstrong ,  University of Florida, United States ; (2)  Susanne Bernhardsson , Link€ oping University, Sweden; (3)  Melissa Brouwers ,  McMaster University, Canada ; (4 ) Andr e Bussi eres, McGill University, Canada ; (5)  Margot Fleuren , Organisation for Applied Scientific Research TNO, Netherlands; (6)  Kari Gali ,  Case Western Reserve University, United States ; (7)  Sue Huckson ,  Australian and New Zealand Intensive Care Society, Australia ; (8)  Stephanie Jones ,  American Academy of OtolaryngologyeHead and Neck Surgery , United States; (9)  Sandra Zelman Lewis , EBQ Consulting, United States; (10)  Roberta James ,  Scottish Intercollegiate Guidelines Network, United Kingdom ; ( 11 )  Catherine Marshall , Guideline and Health Sector Consultant, New Zealand; and ( 12 )  Danielle Mazza ,  Monash University, Australia.
Background: IMGT®, the international ImMunoGeneTics information system® (http://www. imgt. org), was created in 1989 in Montpellier, France (CNRS and Montpellier University) to manage the huge and complex diversity of the antigen receptors, and is at the origin of immunoinformatics, a science at the interface between immunogenetics and bioinformatics. Immunoglobulins (IG) or antibodies and T cell receptors (TR) are managed and described in the IMGT® databases and tools at the level of receptor, chain and domain. The analysis of the IG and TR variable (V) domain rearranged nucleotide sequences is performed by IMGT/V-QUEST (online since 1997, 50 sequences per batch) and, for next generation sequencing (NGS), by IMGT/HighV-QUEST, the high throughput version of IMGT/V-QUEST (portal begun in 2010, 500,000 sequences per batch).
IMGT® comprises 7 databases, seventeen online tools and more than 20,000 pages of Web resources, available at the IMGT® Home page  [4, 5]. The databases provide IMGT biocurated and standardized information on genes (IMGT/GENE-DB  [20] , sequences (IMGT/LIGM-DB  [21] , IMGT/PRIMER-DB), twodimensional (2D) and three-dimensional (3D) structures (IMGT/2Dstructure-DB and IMGT/3Dstructure-DB  [22, 23] ), therapeutic monoclonal antibodies, fusion proteins for immune applications (FPIA), composite proteins for clinical applications (CPCA) and related proteins of the immune system (RPI) (IMGT/mAb-DB  [4] ). The online tools are available for the analysis of nucleotide sequences (IMGT/V-QUEST  [24] [25] [26] , IMGT/Junctio-nAnalysis  [27, 28] , IMGT/Automat  [29, 30] ), next generation sequencing (NGS) nucleotide sequences (IMGT/HighV-QUEST  [31] [32] [33] [34] [35] ), amino acid sequences (IMGT/DomainGapAlign  [36] , IMGT/Collier-de-Perles  [37] ), genes (IMGT/GeneInfo  [38] , IMGT/LIGMotif  [39] , IMGT/GeneFrequency) and 2D and 3D structures (IMGT/StructuralQuery).
The standalone tool, IMGT/ StatClonotype  [40, 41] , allows statistical comparison of clonotype diversity and expression from IMGT/HighV-QUEST NGS results. IG and TR are managed and described in the IMGT® databases and tools at the level of receptor, chain and domain  [1]. A complete IgG1 is made of 12 domains belonging to two identical heavy (H) chains (4 domains each) and two identical light (L) chains (2 domains each)  [1]. The N-terminal domain of each IG H and L chain is a variable domain (VH and VL, respectively) which results from the rearrangement at the DNA level of three genes for the VH (variable (V), diversity (D) and joining (J)) and of two genes for the VL (V and J). As a result a VH is encoded by a V-D-J-REGION whereas a VL is encoded by a V-J-REGION (Table  1 )  [2]. Similarly the N-terminal domain of each chain of a T cell receptor (TR) is a variable domain encoded by a V-D-J-REGION or a V-J-REGION (Table  1 )  [3].
IMGT/V-QUEST Synthesis view results for scFv The top of the page IMGT/V-QUEST Synthesis view results for scFv (Fig. 5 ) recalls, as for the Detailed view results above, the IMGT/V-QUEST program version, IMGT/V-QUEST reference directory release, and then Fig. 3  IMGT/V-QUEST Search page. The analysis of scFv is an option of IMGT/V-QUEST available in the section Advanced functionalities at the bottom of the IMGT/V-QUEST Search page. This option is not selected by default  IMGT/V-QUEST Excel file or IMGT/HighV-QUEST CSV files results for scFv Classically, the IMGT/V-QUEST Excel file or, for NGS, the IMGT/HighV-QUEST comma separated values (CSV) files results include eleven Excel spreadsheets or CSV files, respectively  [35]. Typically, the first ten Excel spreadsheets and CSV files include one line per identified and analyzed V-(D)-J-REGION (V-DOMAIN) (for scFv, there are therefore two lines corresponding to the two V domains for each scFv).
In order to facilitate data extraction and reuse, VH, V-BETA and V-DELTA are in the "1_" column set for scFv which contain paired VH-VL (V-KAPPA or V-LAMBDA), V-ALPHA-V-BETA or V-GAMMA-V-DELTA (Table  2 ). The IG scFv are usually made of a VH and of VL. The order of the V-DOMAIN in an scFv can be either VHlinker-VL or VL-linker-VH. Both V domains of an scFv are transcribed in a single chain and are necessarily in the same orientation of transcription. Different associations of V domains (the two domains being in the same orientation) are possible for the IG or for the TR. Analysis of scFv V-DOMAIN by IMGT/V-QUEST is done against a single species. For the TR, other V domain associations per permutation between any two V domains (not shown) are also analyzable. It should be noted that sequences not identified as scFv (i.
Acknowledgements We thank  Gisèle Clofent-Sanchez  and  Audrey Hemadou  for scFv sequences samples and their implication in the development of the project. We are grateful to  Gérard Lefranc , for helpful comments and to the IMGT team members for their constant motivation. We thank  Géraldine Folch ,  Joumana Jabado-Michaloud ,  Safa Aouinti ,  Mélissa Cambon ,  Imène Chently ,  Karthik Kalyan ,  Anjana Kushwaha ,  Arthur Lavoie ,  Claudio Lorenzi ,  Perrine Pégorier ,  Laurène Picandet ,  Saida Hadi-Saljoqi ,  Mélanie Arrivet ,  Pascal Bento  and  Marine Peralta. IMGT® is Academic Institutional Member of the  International Medical Informatics Association (IMIA)  and of the  Global Alliance  for the Genomics and Health (GA4GH). Funding IMGT® is currently supported by the  Centre National de la Recherche Scientifique (CNRS) ; the  Ministère de l′Enseignement Supérieur et de la Recherche (MESR) ; the  Montpellier University, France ; the  Agence Nationale de la Recherche (ANR)   Labex MabImprove  [ ANR-10-LABX-5301 ];  BioCampus Montpellier ;  Région Languedoc-Roussillon  ( Grand Plateau Technique pour la Recherche (GPTR) ).
Revised: 28 June 2017 -Accepted: 30 June 2017 -Published: 24 July 2017 Abstract. The temporal evolution of a surface chlorophyll a bloom sampled in the western tropical South Pacific during the 2015 Oligotrophy to UlTra-oligotrophy PACific Experiment (OUTPACE) cruise is examined. This region is usually characterized by largely oligotrophic conditions, i. e. low concentrations of inorganic nutrients at the surface and deep chlorophyll a maxima. Therefore, the presence of a surface bloom represents a significant perturbation from the mean ecological state. Combining in situ and remote sensing datasets, we characterize both the bloom's biogeochemical properties and the physical circulation responsible for structuring it. Biogeochemical observations of the bloom document the bloom itself, a subsequent decrease of surface chlorophyll a, significantly reduced surface phosphate concentrations relative to subtropical gyre water farther east, and a physical decoupling of chlorophyll a from a deep nitracline.
In the WTSP, the SPG's northern limb, the South Equatorial Current (SEC), flows west into the Melanesian Archipelago group (MA)  (Chaigneau and Pizarro, 2005). Though the SEC is relatively oligotrophic throughout, the depth of the DCM shoals as it moves west past these island groups, indicative of reduced oligotrophy. Sampling of this zonal gradient was the focus of the Oligotrophy to UlTra-oligotrophy PACific Experiment (OUTPACE) cruise during austral summer 2015 aboard the RV L'Atalante  (Moutin and Bonnet, 2015). The main biogeochemical goals of OUTPACE concerned the study of biological production and its fate in a gradient of trophic conditions, from the ultra-oligotrophic conditions of the SPG to the oligotrophic conditions of the MA  (Moutin et al. , 2017). During the cruise, however, a strong surface chl a bloom was detected from satellite data and intensively sampled for 5 days during long-duration (LD) station LDB.
Cruise sampling plan and context In situ data for this study come from the OUTPACE cruise, conducted from 18 February to 3 April 2015 in the WTSP on the French RV L'Atalante. Over a mostly zonal transect beginning west of New Caledonia and ending near Tahiti (Fig. 1 ), the ship sampled in two main ways: first, the shortduration (SD) stations and, second, the LD stations. For the 15 SD stations, referred to by their number in chronological order, conductivity-temperature-depth (CTD) casts and biogeochemical measurements were taken over a 24 h period, as described in  Moutin et al. (2017, this special issue). During the three LD stations, referred to as stations LDA, LDB, and LDC, a quasi-Lagrangian drift array was deployed with sediment traps. The ship largely followed the trajectory of this array.
Multiple CTD casts were performed, spaced every 3 h. The position of each station was chosen using the SPASSO software suite  (Doglioli, 2013) , which analyzes near-realtime remote sensing data so that an onshore collaborator can provide daily updates regarding the location of possible coherent structures such as eddies  (Doglioli et al. , 2013). Station LDB was selected because of the large surface chl a signal as seen from satellites (Fig. 1b ). The data used specifically in this study were derived from SD12, LDB, and SD13. For these purposes, we defined the general region of interest as 184-192 • E and 22-16 • S (Fig. 1b ). In situ sampling for SD12, LDB, and SD13 took place during 11-12, 14-20, and 21 March 2015, respectively. Before the deployment of the drift array during LDB, a survey of the area was conducted by a Moving Vessel Profiler (MVP; Brooke Oceanographic) platform, allowing for highresolution CTD profiles over three separate transects (T1,T2, and T3 in Fig.
CTD, bottle data, MLD, and nitracline depth The shipboard CTD rosette was deployed four times at SD12, 47 times during LDB, and once for SD13. The rosette layout was the Sea-Bird SBE 9plus CTD rosette, with two CTDs installed on the rosette and a chl a fluorometer (Chelsea Aqua 3). CTD data were calibrated and processed post-cruise using Sea-Bird Electronics software into 1 m bins. Chl a fluorescence was calibrated to chl a extractions taken from bottle samples throughout the cruise. No corrections were made for the daily oscillations due to non-photochemical quenching. Subsequent to CTD processing and calibration, each profile's density was reordered to be stable so that small residual overturns were removed. Casts were spaced approximately 3 h apart, so density and chl a were interpolated to a regular 3 h interval using cubic polynomials.
A horizontal smoothing of density was performed using a locally weighted scatterplot smoothing (LOWESS) filter with a window of four data points, equivalent to 12 h. This time span, designed to remove some internal waves, is about one-third of the inertial period (∼ 36 h) and does not remove the movements present due to near-inertial oscillations, a dominant signature in the shipboard acoustic doppler current profiler (SADCP) data  (Bouruet-Aubertot et al. , 2017, this special issue). Mixed layer depth (MLD) was calculated using a threshold density deviation of 0. 03 kg m -3 from the value at a reference depth. The CTD profiles post-calibration did not always contain surface values, so a 10 m reference depth was used, similar to  (de Boyer Montégut et al. , 2004). Measurements of dissolved nitrate and phosphate concentrations were conducted for two casts at SD12, seven casts at LDB, and the single cast of SD13.
MVP The MVP was used during four transects, three (T1-T3) before LDB and one after (T4) (Fig. 2a ). Prior to LDB, we have T1, going northwest to southeast; T2, going south to north; and T3, going north to south in the same path as T2. For these three transects, a total of 388 casts spanning ∼ 700 km distance were obtained, producing an average horizontal resolution of ∼ 2 km. Subsequent to LDB, T4 traveled west to east from LDB's position, resulting in 95 casts over ∼ 170 km horizontal distance. The MVP vehicle sampled vertically by freewheeling the synthetic cable attached to the MVP fish, allowing for a nearvertical descent at ∼ 4 m s -1. At a prescribed depth (here, 350 dBar), the brake was applied to the computer-controlled winch and the fish automatically brought back to the surface. Only downcasts were used in this dataset due to the deployment method.
S2 , ρ = 0. 998, r 2 = 0. 996). A previous study utilizing MVP data found an operational threshold binning of ∼ 1 m in the vertical  (Li et al. , 2012) , which we followed here. Temperature and calculated salinity were calibrated to the station SD13 CTD cast made adjacent to and soon after the last MVP profile of T4. Chl a values were calculated by calibrating to the already calibrated CTD fluorometer values for SD13, as well. MVP density profiles, as with CTD data, were first reordered to be statically stable. In contrast to the CTD data, horizontal distance, and not time, is the relevant variable. As discussed below (Sect. 2. 4), the stratification was such that, even at 2 km resolution, density structures associated with balanced currents near the surface might be missed, so no additional filtering was applied to density in the MVP dataset despite possible aliasing of internal waves.
The Ri g num-ber analysis detailed in Sect. 2. 4 can be sensitive to these aliased waves and possibly bias the results. While, in general, this processing step should be considered, sensitivity analysis shown in the Supplement (Fig. S3 ) revealed that the lack of filtering with the current dataset did not affect the resulting conclusions. In order to determine when the ship was in the surface bloom, a threshold value was chosen. Inspection of chl a in the upper 20 m revealed a bimodal distribution. As a result, the value of 0. 13 µg L -1 , well above the lower mode and representing the 66 % value of the cumulative distribution function, was selected. Therefore, by our definition the MVP entered the surface bloom when the average value of chl a in the top 20 m surpassed this value. Additionally, the MLD for the MVP transects were calculated from the same method as the CTD casts, by finding the depth where density surpasses 0.
SADCP The RV L'Atalante has two SADCPs, RDI Ocean Surveyors with frequencies of 75 and 150 kHz. In order to maximize vertical resolution, we use the 150 kHz data in this study. Single ping data were collected into 2 min intervals, with vertical bins spanning 8 m. Binned data were processed with the Cascade (Le  Bot et al. , 2011)  software package provided by IFREMER. The Cascade procedure corrects for, among other quantities, the horizontal SADCP-navigation misalignment as well as misalignment of the horizontal plane due to ship roll. In addition, within Cascade the barotropic tidal component was removed using the TOPEX/POSEIDON inverse model  (Egbert et al. , 1994).
Remote sensing data Satellite-derived data (e. g. u, v, sea surface height, and surface chl a) from altimetry and ocean color data were produced specifically for OUTPACE in the WTSP by Ssalto/Duacs and CLS with support from CNES. The procedures used to generate the data are similar to those described in d  'Ovidio et al. (2015) , with the result that these products provide higher resolution and quality control measures than is typically available from global products. As described in the following paragraphs, some of these products were produced post-cruise in delayed time, while others were provided during the cruise in near-real time. Maps of altimetry were generated delayed time by merging along-track observations from the Jason-2, SARAL/AltiKa, CryoSat-2, and HY-2A missions. The regional OUTPACE domain spans 140 to 220 • E, and 30 • S to the Equator, over the yearlong period of June 2014 to May 2015.