dataesr/scientific-paragraphs-categorization huggingface dataset:
Evaluation In order to evaluate system performance, we annotated development and test data as discussed in the "Annotation" section. For this we used 1168 reports from the Edinburgh Stroke Study (ESS)  [22]. We reserved the Manual annotation of the development data was accomplished in six tranches, where annotation was correction of the system output. The system was modified and improved between the tranches. Table  1  provides information on the sizes of the data subsets. The first three tranches were doubly annotated by the radiology experts so that IAA could be monitored. For these three tranches only, disagreements between the annotators were reconciled to produce an agreed gold standard. The remaining development data was singly annotated. The test data was doubly annotated in three tranches but not reconciled.
Conclusion We have described the development and evaluation of the EdIE-R system on brain imaging radiology reports from the Edinburgh Stroke Study. The evaluation results are encouraging and the system is sufficiently accurate that we believe it can be used for its intended purpose of data provision for epidemiological studies. To that end, we are currently testing and revising the system on a dataset of over 150,000 routine brain scans from NHS Tayside collected between 1994 and 2015. We are also in the process of evaluating whether the system can reliably identify cases of intracerebral haemorrhage in patients in Greater Manchester. The evaluation of EdIE-R against these larger datasets will show how robust it is against new data. The disadvantage of a rule-based system such as EdIE-R is that it takes time to write the rules.
Funding Alex and Grover are supported by  Turing Fellowships  from  The Alan Turing Institute  ( EPSRC grant   EP/N510129/1 ). Sudlow is Chief Scientist of  UK Biobank  and Director of  Health Data Research UK Scotland. Mair is supported by a  Stroke Association Edith Murphy Foundation Senior Clinical Lectureship  ( SA L-SMP 18\1000 ). Whiteley was supported by an  MRC   Clinician Scientist Award  ( G0902303 ) and is supported by a  Scottish Senior Clinical Fellowship  ( CAF/17/01 ). Publication costs are funded by the  RCUK Open Access Fund.
Availability of data and materials The annotated ESS corpus that we have created as part of this project has much potential value as a resource for developing text mining algorithms. This data will be available on application to Prof. Cathie Sudlow (email: Cathie. Sudlow AT ed. ac. uk) to bona fide researchers with a clear analysis plan, in line with the Wellcome Trust policy on data-sharing (https://wellcome. ac. uk/ what-we-do/topics/data-sharing). We are in the process of creating a release of EdIE-R free for research purposes (https://www. ltg. ed. ac. uk/software/edie-r). For more information contact Dr. Beatrice Alex (email: balex AT ed. ac. uk).
FLS growth dynamics and theoretical framework To draw a connection between the heterogeneity of actin regulators inside FLS tip complexes and the observed exponential length distribution, we developed a theoretical framework to describe FLS length dynamics. We applied this to the lengths of large numbers (>100,000) of individual FLS measured with high time resolution (Fig. 2A, B). By analogy to a study of lamellipodia dynamics  (37) , after an initial rapid growth phase, the FLS length cycles between elongation and retraction phases (Video 1, Fig. 2A ). From these data, we calculated histograms of growth velocities, which had exponential tails both in positive (growth) and negative (shrinkage) directions and were largely symmetric. This bi-exponential shape is a Laplace distribution, which fits the data to a remarkable degree (Fig.
Product terms can arise from complex-forming molecular reactions  ! +  ! →  !  ! , with the complex  !  ! producing FLS elongation or shrinkage, while the sums represent the independent effect of two complexes  !  ! and  !  ! on velocity. When fluctuations are large compared to baseline concentrations, this provides a simple framework in which Laplace distributions can emerge from stochastic protein dynamics (see supplementary information for details). The dynamics of the concentration fluctuations X are controlled by a single parameter, the relaxation rate , which determines how quickly a concentration returns to its baseline after a random change. Based on this model, we could simulate velocity trajectories and, via numerical integration, FLS length trajectories (Fig. 2C ). We collected length data points at the 20-minute time point, both in our simulations and in our segmented trajectories.
Chemical labelling of proteins with fluorescent dyes Labelling of SNAP-tagged recombinantly expressed proteins (6His-SNAP-Toca, 6His-mKate-GBD, 6His-SNAP-Ena, 6His-SNAP-N-WASP/ZZ-WIP) were performed with 5-10 µM final protein concentration and 10 µM dye (SNAP-Surface Alexa Fluor488 (New England Biolabs S9129S) or SNAP-Surface Alexa Fluor647 (New England Biolabs (2. 97×2. 97 µm) (e. g. four FLS tips and four corresponding background regions) were selected. Five frames were recorded in 1 second intervals prior to bleaching using the 488 nm or 561 nm laser at 25% power for two iterations. Fluorescence recovery was recorded by the corresponding laser line at 5% laser power for 120 frames, with intervals of 0. 5 sec for the first 40 frames and 1 sec for all following frames. Changes in fluorescence intensity in the ROI after photobleaching were analyzed in ImageJ using a publicly available script developed at the Image Processing School Pilsen 2009 according procedures previously described  (46).
Post processing of snapshot data We filter out segmented FLS with an effective diameter of less than 0. 5 µm because base size information as well as fluorescent intensity measurements become unreliable at or below the resolution limit. When considering FLS length distributions, we truncated the distribution to lengths between 5 µm and 20 µm to exclude structures which have not yet matured into FLS and artefacts stemming from the lower z-resolution in our confocal stacks. Fluorescence intensities of observed tagged proteins are determined by subtracting the local background intensity from the intensity averaged over all pixels in the FLS base area. To determine protein-protein and protein-morphology correlations, we calculate the Spearman correlation values for each field of view separately and average over the resulting ensemble.
Live imaging and data analysis of Drosophila embryo filopodia As previously described (42) dechorionated embryos (washed in 50% bleach) were mounted on a glass-bottomed dish with heptane glue and submerged in water. To identify GFP-ena homozygous embryos balancer chromosome CyO with Dfd-YFP were used and we did negative selections for Dfd-YFP expression in the head region of embryos. Live microscopy was performed on an inverted Leica TCS-SP5 equipped with a 63x 1. 4 NA Plan Apo oil immersion objective at room temperature. To visualize filopodial movement and respective protein intensities within filopodia in dorsal closure, embryos were imaged at the end of stage 14. Microscopic measurements were performed by taking z-stacks of 7-11 z sections (0. 5 µm spacing). Time-lapses were takes at 15 second intervals for 10 min.
X. tropicalis TOCA-1 (accession number BC080954) was PCR amplified from IMAGE clone 6980375 (Source Bioscience), and cloned into pET SNAP precision FA. X. tropicalis N-WASP (WASL) (accession number BC067309) was PCR amplified from IMAGE clone 5379332 (Source Bioscience), and cloned into pCS2-his-SNAP-FA. ZZ-TEV-WIP (Ho et al. , 2004) was a kind gift from the Kirschner lab (Harvard, USA). X. laevis VASP (accession number BC077932) was PCR amplified from IMAGE clone 5515353 and cloned into pET SNAP precision FA with additional residues KCK added before the ATG, and site directed mutagenesis at GA192/193 to destroy endogenous cysteine. X. laevis Ena (accession number BC073107) was PCR amplified from IMAGE clone 5379332 and cloned into pCS2 his SNAP acceptor. X. laevis fascin (accession number BC097600) was PCR amplified from IMAGE clone 4970584 and cloned into pCS2 his GFP (GFP was PCR amplified flanked with ecoRI/fseI restriction sites and cloned into pCS2 his FA acceptor).
Acknowledgments We would like to thank  Bishara Marzook ,  Helen Fox  and  Louise Whiteley  for protein preparation and immunodepletion assistance,  Vivek Bhogadi  and  Sven Huelsmann  in the creation of fascin and Ena GFP fly stocks and  Nick Brown ,  Helen Mott ,  David Owen ,  Sandra Schmid  and  Marc Kirschner  for critical reading of the manuscript. We thank the  Gurdon Institute imaging facility  for microscopy support. We dedicate this work to  Guilherme Correia (Will)  who started this project for his PhD and was tragically unable to.
The evolution of human-specific lateralised functions such as language has been linked to the development of structural asymmetries in the brain. Here we applied state of the art image analysis techniques to measure Sylvian Fissure (SF) asymmetry and Occipital Bending (OB) in 3D Magnetic Resonance (MR) images of the brain obtained in-vivo for 27 humans and 29 chimpanzees (Pan troglodytes). SF morphology differed between species, with the human SF terminating more superiorly in right inferior parietal lobe, an asymmetry that was on average absent in chimpanzees (F (1,52) = 10. 692, p = 0. 002). Irrespective of morphology, Total SF Length was, as previously reported, leftward in humans but not in chimpanzees, although the difference did not reach significance between species. However, when only brains possessing comparable bilateral SF bifurcation morphology were compared, humans showed previously reported left-lateralised Anterior-Horizontal (AH-SF) and right-lateralised Vertical (V-SF) SF asymmetries.
, 1999; Horn et al. , 2009 ), Heschl's Gyrus  (Shergill et al. , 2000; Dorsaint-Pierre, 2006) , and underlying Arcuate Fasciculus white matter tract  (Takao et al. , 2011)  which are all left-lateralised. However, the relationship between structural and functional brain asymmetry is not simple (see  Dorsaint-Pierre, 2006; Keller et al. , 2011) , the region is associated with language comprehension and production  (Boeckx and Benítez-Burraco, 2014)  and auditory processing (e. g. Johnsrude et al. , 1997). Posteriorly, the SF bifurcates in the inferior parietal lobe with the Vertical SF (V-SF) segment (the Posterior Ascending Ramus, Figure  1 ) reported to be longer, and terminate more superiorly, in the right hemisphere  (Rubens et al. , 1976; Witelson and Kigar, 1992). Associated with the Planum Parietale (PP,  Jäncke et al.
The present study is the first to measure SF asymmetry (both morphology and length) and OB in humans and chimpanzees and uses advanced image-processing tools available in Freesurfer  (Dale et al. , 1999; freesurfer. net) , FSL  (Smith et al. , 2004; fsl. fmrib. ox. ac. uk)  and BrainVISA  (Fischer et al. , 2012; brainvisa. info) software. Measuring SF asymmetry and OB will determine if there is also a joint asymmetry of these components in chimpanzees. This analysis can potentially inform on whether OB and SF asymmetries evolved together (i. e. concerted evolution) or independently (i. e. mosaic evolution)  (Reyes and Sherwood, 2015)  and secondly, whether the asymmetries emerged before the divergence of humans as a conserved trait, or developed uniquely in humans. We hypothesise that the majority of humans show a default pattern of lateralised SF asymmetry that is related to rightward OB, both of which are lacking in chimpanzees.
The chimpanzee scanning followed YNPRC standard procedure, with subjects first being immobilised through ketamine injections (10mg/kg) and anesthetized with propofol (40-60 mg. kg -1. h -1 ). Subjects were transported from and back to their home environment and imaging facilities (total time ~ 2 hours) and scanned whilst remaining anesthetized. Scanning was conducted with the chimpanzee's head placed in a human head-coil in the supine position. The archived MRI data were uploaded onto a computer for pre-processing and analysis.
The resulting brain segmentations and masks were imported into BrainVISA's Morphologist Pipeline 2012 (Version 4. 4. 4) to generate and automatically label 3D sulcal graph folds. The SF labels were visually checked and manually corrected using BrainVISA's visualisation software Anatomist. These steps are demonstrated in Figure  2. M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 6 2. 3 Sylvian Fissure Morphology and Processing.
Sylvian Fissure Anatomy Human and chimpanzee MR images were inspected using BrainVISA software to identify the key SF landmarks in 3D (Figure  1 ) the Anterior Bifurcation Point (A), the Termination Point of the PAR (S1) and, when present, the Posterior Bifurcation Point (B). In particular, (A) is determined as the point where the anterior ascending ramus and anterior horizontal ramus join the SF  (Ono et al 1990) , (S1) is the posterior limit of the SF and (B) is the point where the SF may branch into the PAR and PDR. Furthermore, (B) splits the SF into an Anterior-Horizontal SF segment (AH-SF) (i. e. from landmarks A to B, Figure  1 ) and the PAR forms the Posterior Vertical SF segment (V-SF) (i. e. from landmarks B to S1, Figure  1 ). PDR orientation was used to determine Bifurcation Types (see below), but as in  Witelson and Kigar (1992) , the length of the PDR was not measured.
Sylvian Fissure Sulcal Mesh Processing All scans were checked to ensure that each landmark was correctly identified by the software so as to enable the accurate labelling and measurement of both the AH-SF and V-SF aspects if present. Landmark (B) was often missed by the software, and therefore was manually identified and used to split the SF sulcal fold accordingly. In particular, a method was developed using the Anatomist Software tool kits cross-referencing landmark (B) at three different sagittal depths to ensure 3D morphology was respected. The SplitFold tool was used to cut the SF mesh surface along the line joining these three landmarks so as to generate two separate 3D meshes corresponding to the V-SF and AH-SF (Figure  3 ).
Statistical Analysis For each species, one-way t-tests were used to determine whether AI was significantly asymmetric in either direction for Total SF Length and Trajectory in the Whole Cohort and additionally for AH-SF and V-SF length and positions in the Bilateral Bifurcation Cohort. Between-species differences in SF length, Bifurcation position and OB were examined using one of two approaches. If the data fulfilled the criteria of equal homogeneity of variances for parametric tests, a MANCOVA analysis was performed with sex and age as a covariate. If the data were non-parametric an Independent-Samples Mann-Whitney U-Test was performed. Population distribution differences in OB, Bifurcation Type, Bifurcation Trajectory and SF length were compared using Chi-squared analysis. Statistical analysis was conducted using SPSS Statistics (version 20.
M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 10 = 2. 365, p = 0. 059, ns) and V-SF (F (1, 34) = 1. 881, p = 0. 179, ns) or Total-SF (F (1, 34) = 0. 728, p = 0. 399, ns) length asymmetries did not reach statistical difference (Table  4 , Figure  6 (ii)). Analyses of patterns of AH-SF and V-SF within individual brains showed that of the humans with bilateral bifurcations, 15/24 (62. 5%) had the Typical pattern of SF asymmetries whereas only 3/24 (12. 5%) had the Reversed pattern. Only 5/14 of the chimpanzees with bilateral bifurcations had the Typical pattern (35. 7%) and 3/14 (21. 4%) had the reversed SF patterns. The remaining subjects (6/14) showed a mixed phenotype, however, the difference in distributions between species did not reach statistical significance (χ 2 (2, n: 38) = 2.
SF Asymmetries (length) When the SF is bifurcated bilaterally, humans show the Typical asymmetry pattern (i. e. leftward AH-SF and rightward V-SF length) as previously reported  (Witelson and Kigar, 1992). This pattern is M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 13 found in just under two-thirds of individual brains (62. 5%). In contrast, only 35. 7% of chimpanzees in the equivalent bilateral bifurcation cohort had the Typical SF pattern, and neither AF-SF nor V-SF was lateralised in chimpanzees as a whole. Although the results of the present study appear to contradict previous findings that chimpanzee SF length is asymmetric (e. g. Yeni-Komshian and Benson, 1976; Hopkins, Pilcher and MacGregor, 2000; Cantatupo, Pilcher and Hopkins, 2003; Bogarts et al. , 2012) , previous studies did not use the same anatomical landmarks or protocol to measure AH-SF and V-SF individually.
, 2010) , and development of human-specific regions (e. g. PFm;  Krubitzer, 2009; Caspers et al. 2011). Although laterality was not explicitly studied in these reports, the angular aspect of the human inferior parietal gyrus is reported to be larger on the right  (Goldberg et al. , 2013) , raising the possibility that the higher termination and shortening in length of the right SF characteristic of the human brain may be a biomarker of an asymmetrically expanded IPL. The observed differences in the structural asymmetry of the human and chimpanzee brain are particularly relevant within an evolutionary context as they potentially reflect regional functional reorganisation  (Caspers et al. , 2011; reviewed in Binkofski, Klann and Caspers, 2016)  of networks involved in both language and motor planning/gesture in humans, through the left-lateralised Arcuate Fasciculus (AF,  Rilling, 2014)  and right-lateralised Superior Longitudinal Fasciculus (branch III,  Hecht et al.
Limitations The modest sample size is a limitation of this study, particularly as the low proportion of chimpanzees with bilateral bifurcations reduces the ability to measure the significance of AH-SF and V-SF asymmetry, and individual t-tests for asymmetry direction and correlational analyses were not corrected for multiple comparisons. This also prevented the independent consideration of sex M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT differences, with previous work suggesting that both the SF  (Witelson and Kigar, 1992; Taglialatela et al. , 2007)  and OB asymmetries  (Maller et al. 2014 ) exhibit sex differences (though see  Narr et al. 2007). Sex was not a significant covariate in either SF or OB measures although a larger study is required to specifically address this point.
We discuss the simplified likelihood framework as a systematic approximation scheme for experimental likelihoods such as those originating from LHC experiments. We develop the simplified likelihood from the Central Limit Theorem keeping the next-toleading term in the large N expansion to correctly account for asymmetries. Moreover, we present an efficient method to compute the parameters of the simplified likelihood from Monte Carlo simulations. The approach is validated using a realistic LHC-like analysis, and the limits of the approximation are explored. Finally, we discuss how the simplified likelihood data can be conveniently released in the HepData error source format and automatically built from it, making this framework a convenient tool to transmit realistic experimental likelihoods to the community.
JHEP04(2019)064 The simplified likelihood (SL) framework we present in this paper is a well-defined approximation scheme for experimental likelihoods. It can be used to ease subsequent numerical treatment like the computation of confidence limits, to allow a uniform statistical treatment of published search-analysis data and to ease the transmission of results between an experiment and the scientific community. We build on the proposals for approximating likelihoods recently suggested in refs. [1, 2] , in which promising preliminary results have been shown. In the context of the LHC, communicating the experimental likelihoods, in their full form or in convenient approximations, was advocated in refs. [3, 4]. One possibility is to communicate the full experimental likelihoods via the RooFit/Roostats software framework  [5, 6].
Technically this is done by taking into account the next-to-leading term in the limit given by an appropriate version of the Central Limit Theorem (CLT). The paper is organised as follows. Section 2 introduces the formalism and key points of our approach. The formal material, including an in-depth discussion of the next-toleading term of the CLT and the derivation of the SL formula, is presented in section 3. Practical considerations regarding the SL flexibility and the release of the SL via HepData are given in section 4. Finally a validation of the SL framework in a realistic pseudo-search at the LHC is presented in section 5. Section 6 contains our summary and conclusions. Two appendices give some more useful details: appendix A contains a 1D example of how the skew appears in the asymptotic distribution, and appendix B presents a reference implementation of the SL written in Python.
2 From the experimental likelihood to the simplified likelihood This section introduces the formalism and an efficient Monte-Carlo based calculation method. Some preliminary remarks are in order. From the conceptual point of view, the SL framework relies only on the convergence of the CLT. In practice however, the representation of the SL will depend on broad, structural features of the dataset under consideration. The case considered in this paper is a set of P independent observables in the presence of N independent sources of uncertainties, with N ≥ P. For a dataset with different structure, the SL would take a different form, but this is not a fundamental lim-JHEP04(2019)064 itation of the approach per se. Moreover, in the scope of a given problem, e. g. the search for new physics in our case, additional approximations may simplify the formalism.
Moreover, in the case where the nuisance parameters affect only the background rate eq. (2. 4) , this computation has to be realised only once and the resulting likelihood can be used for any kind of signal by appropriate substitution of n s (α). A reference code implementing the SL and subsequent test statistics is described in appendix B and publicly available at https://gitlab. cern. ch/SimplifiedLikelihood/SLtools. 3  The simplified likelihood from the central limit theorem This section contains the derivation of the SL formula eq. (2. 3). The reader interested only in the practical aspects of the SL framework can safely skip it. In section 3. 1 we lay down a result about the next-to-leading term of the CLT. In section 3. 2 we then demonstrate eq. (2. 3) and give the analytical expressions of the SL parameters as a function of the elementary uncertainties.
JHEP04(2019)064 While the former is in principle doable, we will focus only on the latter. Indeed, the elementary uncertainties are usually already coded by the experimentalists in MC generators, hence it is straightforward to evaluate these moments. 6  We thus focus on the release of the SL data via the m 1,I , m 2,IJ , m 3,I moments of the PDF of the combined systematic uncertainties, already defined in eqs. (2. 6)-(2. 8), where m 3,I is the diagonal part of the third-rank tensor m 3,IJK. Evaluating these moments via MC toys is straightforward for the experimental analysis. However, their way of presentation needs to be considered in detail, taking into account the available tools and the current practices. This is the purpose of this subsection. Key to the usefulness of any likelihood data for analysis reinterpretation is the availability of that data in a standard format.