dataesr/scientific-paragraphs-categorization huggingface dataset:
Data The duration of each phase differed according to the patient's responses to the therapy. For horse behaviors, the proportion of the frequency over the duration of the given phase was calculated to standardize this variable among different phases. Finally, the frequency of each behavior per minute (freq/min) was considered for the statistical analysis. HRV data were analyzed as raw data to compare the differences between the two EAT phases and between the two categories of patients' therapy expectations. Then, the differences (∆) between the preparation and resting phases and between the working and resting phases were calculated to study the evolution of these parameters from resting to the two different EAT situations. These parameters were defined as ∆HR, ∆VLF, and ∆LF/HF ratio.
In one working phase, a side walker was required to ensure the patient's safety. This unexpected situation clearly modified the horse's behavior. As some behavioral or HRV parameters were influenced by this condition, the authors decided to remove them from the statistical analysis (EPB, HLM, LF/HF ratio, and ∆LF/HF ratio). Due to technical issues related to the heart rate monitor, the HRV data of two horses in the working phase were not recorded.
The parameters of the laws were estimated based on French databases and the scientific literature. The SIGAL database (centralized national database of the ministry of food and agriculture) provided data concerning the surveillance and control interventions (screening results and laboratory analyses) in 2016. The national database of cattle identification (BDNI) provided data concerning the distribution of production type, herd size, distribution of age within the herds, and animal movements (sales) in 2016. The categories of farms listed below were defined by the Omar project  (Perrin et al. , 2012)  and were available in the BDNI. We used herd type data from a French department in which each herd type (production type, size, and turnover category) was present and in which the size and proportion of adult cattle were the closest to the National French average for each herd type (data of 1 January 2016 from Cantal, extracted from the BDNI).
Proportion of animals tested Screening generally misses a few adults, primarily for technical reasons (for example, difficult tocontain animals). Based on the SIGAL database, we estimated that between 95% and 99% of adult animals are tested. We thus used a uniform law between 0. 95 and 0. 99 to describe this parameter. The data did not allow differentiation by herd type. In the strict protocol, only a sampling of animals in the suspect herd is generally tested a second time with ICCT. Analysis of the SIGAL database showed a minimum of one adult to be tested a second time and a maximum of 100%. Limited data were available in this database (207 farms) and we detected no significant difference in the mean number of animals tested a second time between herd types. Nevertheless, all animals of most (55%) small herds appeared to be tested a second time with ICCT, whereas the average number of animals tested a second time in big herds was 53.
Post mortem tests results The diagnostic slaughter test results are represented separately in Figure  4 , as the path is the same for each of the three screening protocols studied. The sensitivity and specificity of bTB tests (PCR, bacteriology and histology) were previously estimated depending on the presence of bTB-like lesions  (Courcoul and Boschiroli, 2013). As the CIs of these estimations were asymmetric, we used normal asymmetric distribution laws for the parameters of the scenario tree (Table  4 ). We calculated the proportion of animals with detectable lesions, depending on the infectious status of the animal, using French slaughter data between 2008 and 2012, described by  Courcoul et al. , 2014 (Appendix 2). We hypothesised that the histology was independent of PCR and bacteriology, based on the modelling results of  Courcoul et al.
Costs Costs of surveillance protocols can be direct (screening tests, organisation of the screening campaigns, laboratory analyses, etc. ) or indirect (losses due to the ban of selling animals or unpasteurised milk). In In France, the price of post mortem analyses is different for each laboratory. Thus, we conducted an online survey among the 40 French ADLs in April 2018 with the help of the French association of the directors and executives of veterinary laboratories (ADILVA). We used the results of this survey to estimate the price of each analysis and sample transport fees (Table  6 ). Based on the SIGAL database, we estimated the mean number of samples sent for PCR by an ADL for one animal, depending on the presence of detectable lesions (3. 59 for animals with lesions and 3. 77 for animals without lesions) and the mean number of samples sent for histology by an ADL (1.
9 samples for animals with lesions only). These data and the probability of occurrence of each laboratory analysis allowed us to calculate the mean cost of the diagnostic slaughter for an animal, depending on its infectious status. The State compensates farmers 2,200 € for the slaughter of an adult animal if it is registered in the (1) compensation (€) = (1-herd book inscription rate)*1900 + herd book inscription rate*2200 -meat value We associated a weighted direct cost to each limb of the tree, equal to the corresponding direct cost multiplied by the probability of occurrence of the limb. Then, we calculated the mean direct cost for each protocol by herd type, by adding all weighted costs of the paths corresponding to the considered herd type.
Advantages and limitations of the method Here, we used stochastic scenario-tree modelling to estimate the herd sensitivity and cost of three mandatory investigation protocols in cattle farms for twelve herd types. We used various data sources (published studies, national databases, and expert opinions) and this method allowed us to account for the variability and the uncertainty in those data. The inputs chosen for these models were those with a documented impact on either infection or detection of bTB. Thus, we did not integrate some factors for which the impact was not sufficiently documented to allow their use. For example, the physiological status of the animals (other diseases, pregnancy, age, etc. ) probably has an impact on their reactivity to the ICCT  (Buddle et al. , 2009; Brooks-Pollock et al.
(1) The proportion of doubtful PCR results was estimated for each type of animal (infected or uninfected, with or without lesions) based on the SIGAL data of 2016. In these data, there were no doubtful PCR results for any animals without lesions (infected (74 animals) or uninfected (3,438 animals)). Of the 888 uninfected animals with lesion(s), only one animal showed a doubtful result (equal to 100% of the positive or doubtful results). In 2016, 50% of PCR nonnegative results for the 18 animals infected with lesion(s) were doubtful, whereas 0% of the PCR non-negative result for the 18 animals infected with lesion(s) in 2015 were doubtful. N(44. 24, 15. 04) (1)  Restrained between 1 and 74 (2) ≥ 40% N(28. 88, 16. 25) (1)   big < 40% N(98. 86, 26. 13) (1)  Restrained to be higher than 74 (3) ≥ 40% N(80.
We chose the parameters of the uniform law to describe the daily care costs of this group as the minimum and maximum value among the four estimated. We also grouped the estimation for one and two-year-old heifers into the category "female younger than 24 months". An analyses of BDNI data showed that, in most French beef and beef/fattening farms, there are more heifers under one year of age than heifers between one and two years of age: the mean proportion of heifers under one year of age among heifers younger than two years of age was 64%. We thus estimated the daily care cost of females under 24 months of age as the weighted mean of this cost for a one-year-old heifer and a two-year-old heifer with coefficients of 0. 64 for one-yearolds and 0. 36 for two-year-olds. We obtained a daily care cost of 2.
ACKNOWLEDGEMENTS The authors want to thank the  French Ministry of Agriculture  and the  French Agency for Food, Environmental , and  Occupational Health  and Safety for providing access to the SIGAL and BDNI data. We also thank the ADILVA for their help in administrating the survey among departmental analysis laboratories;  M-L Boschiroli , director of the national reference laboratory for bovine tuberculosis, for providing his insight concerning laboratory tests; and the regional and national bTB coordinators for their help, especially  F. Chevalier  for his validation of some of the parameters. Finally, we thank  William Hempel  from  Alex Edelman and Associates  for the English proofreading of the manuscript. FUNDING The  French Ministry of Agriculture  and the  French Agency for Food, Environmental , and Occupational Health and Safety supported this work.
The French surveillance network for causes of equine mortality (Resumeq) was created in 2015 for the qualitative surveillance of equine mortality through the centralization in a national database of necropsy data and their subsequent epidemiological analysis. It was designed to identify the causes of equine mortality, monitor their evolution over time and space, and detect emerging diseases as early as possible. Resumeq is an event-based surveillance system involving various players and structures. It is organized around a steering body, a scientific and technical support committee and a coordination unit. Different tools have been developed specifically for Resumeq. These include standardized necropsy protocols, a thesaurus for the anatomopathological terms and the causes of equine death, and an interactive web application so that network contributors can display data analysis results.
Several studies relying on post-mortem examinations  (9) (10) (11) (12) (13) (14)  have provided descriptive epidemiological data on the main equine diseases, thus helping to establish current disease trends in different populations and to suggest control and prevention measures. The ANSES Laboratory for Equine Diseases (ANSES-LPE) in Normandy, North West France, has for many years been a reference in the field of necropsies  (11, (15) (16) (17). However, the surveillance data produced was limited to the Normandy region, and to obtain a national picture, it was necessary to change a regional system into a national system. The French surveillance network for causes of equine mortality (Resumeq) was created in 2015 for the qualitative surveillance of equine mortality by centralizing necropsy data in a national database that could be exploited for epidemiological purposes.
Depending on the epidemiological and clinical context, various complementary options are also possible: collection of cerebrospinal fluid, isolation of the head and examination of the brain, guttural pouches and nasal cavities, examination of the spine, and a sagittal section of the hooves. Due to the difficulty of performing a complete post-mortem examination in the field, veterinary practitioners may furthermore use a partial protocol focusing on a specific anatomical region. In any case, the nature of the necropsy protocol used must be specified by the Resumeq members when entering data in the database. Finally, a specific procedure for necropsy examination in the context of abortions and stillbirths has been developed which is valid for all players.
Training Resumeq Members At the same time, emphasis was placed on the initial and ongoing training of network members through the regular organization of training courses and internships to improve their expertise in the diagnosis of the causes of equine mortality. These target not only current network participants, but also potential future members through a partnership with veterinary schools, which propose students who have specialized in the equine sector and/or in pathological anatomy. Short training sessions of between one and three days are organized annually for network members by the coordination unit (ANSES-LPE) and the pathological anatomy unit of the National Veterinary School of Alfort (ENVA). They include practical and theoretical training designed to improve the skills of players in terms of implementing equine necropsy procedures and diagnosing the causes of mortality, as well as entering data in the national database.
). The thesaurus of anatomopathological terms was derived from the reference thesaurus set up by the French SAGIR surveillance network of wildlife mortality  (18) , with members' approval. The thesaurus was then tailored to equines with the help of ENVA. The cooperation between two mortality surveillance networks focusing on different specie offers contributors to both networks a single anatomopathological reference system, thus improving efficiency and quality when entering their data. A glossary for the anatomopathological thesaurus was then developed by ENVA's pathological anatomy unit to help players entering lesional data. Use was furthermore made of ANSES-LPE's experience in diagnosing causes of equine mortality and its own database, which contains necropsy data going back more than 20 years, to classify the causes of mortality according to different main and secondary categories, and led to the creation of a thesaurus dedicated to the causes of equine mortality.
Centralizing and Consolidating Data A Web interface is used by Resumeq contributors to enter their data directly in the dedicated national database. The vast majority of data is entered through drop-down menus. The lesional data and cause of death in particular are entered using drop-down menus applicable to both thesauri in order to obtain standardized data. These data are then consolidated centrally. Partially automated data quality control has been set up to retrieve a list of irregularities on a monthly basis. The quality control is carried out through a dedicated script using R software  (19). This provides information about missing data for all the interface fields and makes it possible to carry out checks for likelihood and coherence (length of the transponder number, date of death < date of necropsy, etc.
Communication and Adding Value to Data Data are regularly analyzed by the coordination unit (ANSES-LPE) and the scientific and technical support structure to identify the main causes of mortality in equines according to different age categories. Tools to communicate results and coordinate network activities were also set up, with the creation of a website (https://sites. anses. fr/fr/minisite/resumeq) and a Web interface developed using the R shiny application  (19)  that allows the interactive display of network results. By regularly updating this interface, players have the very latest feedback, which fosters network dynamics. A biannual newsletter is also published to communicate main network facts and figures, interviews with members and activities, for example. When a potential hazard is identified at a regional or national level, Resumeq uses different channels to disseminate alerts, including the epidemiological surveillance network for equine pathology (RESPE)  (20)  for dissemination to veterinarians and the French Horse and Riding Institute (IFCE)  (21)  for widespread dissemination throughout the French equine sector.
Despite the few years that Resumeq has been running, the temporal description of necropsy submissions has revealed a marked seasonality for fetuses and foals. The period with the highest number of dead foals submitted for necropsy is logically superimposed on the foaling season (increase in the population at risk). Similarly, the lack of fetuses submitted for necropsy in spring can be explained by a reduced number of pregnant mares during this period. These results are consistent with a previous study showing a similar seasonality in equine deaths in France through the temporal description of data from rendering plants, which are centralized in the Fallen Stock Data Interchange (FSDI) database, managed by the French Ministry of Agriculture  (28). In the future, it would be useful to concomitantly monitor the temporal evolution of the total number of dead equines in France through the FSDI database and that of the number of necropsies submitted to the Resumeq network.
On the other hand, the delay prior to data being entered in the database is too long. To reduce this delay, we need to raise the awareness of Resumeq members about the importance of the database as a channel for rapid feedback to the coordination unit. Currently, Resumeq members quickly contact the coordination unit (ANSES-LPE) directly if they come across an abnormal event, and only complete the database afterwards. The delay in data entry does not therefore affect the possibilities of an alert for well-identified individual events. On the other hand, reducing the delay between completion of the necropsy and entry of the corresponding data will be a major point to improve for syndromic surveillance development in the short and medium term (follow-up of unknown etiologies, or of clinical and/or pathological syndromes).
Indicators were considered satisfactory when their values for 2017 reached or exceeded the expected value defined by the Scientific and Technical Committee and validated by the Steering Committee. The indicators used to monitor the network's management, coordination, and training activities are all satisfactory. Feedback and communication were subject to focused developments in 2017, in particular with the creation of a Web interface rolled out in early 2018. The indicator relating to the updating of results via this interface could not be evaluated for 2017 but the monthly update rate target for 2018 has so far been met. The delay in the publication of the second network newsletter explains the low value of the corresponding indicator but has had no effect on network operation. The data quality indicators (proportion of equines with an identification number entered in the database, proportion of equines with a known département during life, proportion of equines with a known département of death, proportion of necropsies with a fully filled in cause of death) are very satisfactory, whereas the value of the indicator relating to the delay prior to data being entered in the database (proportion of necropsies whose data were entered <15 days after the necropsy) is unsatisfactory.
4%) 75. 5% number of départements with necropsy cases / total number Proportion of dead equines necropsied by 1. 5% 287/37,816 (0. 76%) 50% Resumeq: number of necropsy cases / number of equines removed by a fallen stock company in 2017 COLLECTION AND DATA MANAGEMENT Proportion of necropsies whose data entry began ≥60% 57% 95% less than 15 days after the necropsy Proportion of necropsies with a cause of death ≥95% 98. 5% 100% completely filled in Proportion of equines with a known département of ≥95% 99% 100% death Proportion of equines with a known département ≥90% 97% 100% during life Proportion of equines with an identification number ≥90% 90% 100% entered in the database TRAINING Number of training sessions organized 1 1 100% Proportion of VSs and VLs that have followed at ≥80% 80% 100% least one training session within two years of joining Resumeq (VS, veterinary school; VL, veterinary laboratory; VC, veterinary clinic).
The data quality indicators (proportion of equines with an identification number entered in the database, proportion of equines with a known département during life, proportion of equines with a known département of death, proportion of necropsies with a fully filled in cause of death) are very satisfactory, whereas the value of the indicator relating to the delay prior to data being entered in the database (proportion of necropsies whose data were entered <15 days after the necropsy) is unsatisfactory. The value of the indicators relating to network coverage and representativeness in terms of causes of death seem insufficient. In fact, the number of new members is very satisfactory and far exceeds the target set for 2017. The proportion of necropsy centers (veterinary schools or veterinary laboratories) subscribing to Resumeq is reasonable, but the values decrease when focusing on the number of active necropsy centers, that is to say centers having entered necropsy data during 2017.
Recording and analysis of vocalisations Vocalisations produced during handling in the arena were recorded using a high-quality condenser microphone designed for recording ultrasonic vocalisations produced by bats (Pettersson M500-384 USB Ultrasound microphone, Pettersson Electronik; Sweden) and a free recording software (Audacity, Version 2. 1. 3, Pennsylvania, United States of America). The microphone was placed over the centre of the arena, pointing downwards 61. 5 cm from the arena floor. Vocalisations were manually counted from spectrograms produced using Audacity software (Version 2. 1. 3, Pennsylvania, United States of America). Spectrograms were generated with a fast Fourier transform length of 512 points with a Hanning window (50% overlap frame). Only 50kHz vocalisations (peak frequency between 30 and 80 kHz and a duration between 10-150 ms) were counted as the production of 50kHz USVs are associated with positive behaviours and were used as an indicator of positive experience,  (Brudzynski, 2009; Wright et al.
Recording and analysis of hand-following behaviour The behaviour of tickled and control rats in the arena was recorded using a second Sony HD camcorder (HDR-CX405). Observer XT 11 software was used to analyse the duration of hand-following (HF) events during the pause section of each handling session to gain information on approach behaviour  (Lampe et al. , 2017). The duration (in seconds) and counts of hand-following events were calculated for each rat using focal observation sampling with continuous recording. Rats were deemed to be handfollowing when the nose was oriented towards the hand and was actively moving towards the experimenter's hand. The experimenter moved the hand in circles in the same manner for all rats, standardised by counting the number of circles made by the hand, to help assess whether movement towards the hand was intentional  (Melotti et al.
Recording and analysis of play behaviour in the home cage Prior to handling and immediately after being taken to the procedure room, behaviour in the home cage was recorded using a Sony HD camcorder (HDR-CX405) for 5 minutes to measure anticipation of interaction with the handler. Videos were analysed using Observer XT 11 software (Noldus Information Technology, Wageningen, the Netherlands). The frequency of solitary play and the frequency and direction of social play were scored using focal observation sampling with continuous recording (see Table  1  for full ethogram of behaviours scored). Solitary play was scored as a measure of individual play with an event being defined as finished when the rat ceased movement or engaged in behaviours other than the leaps and running described in Table  1 , with the behavioural unit as the number of solitary play events per 5 minutes.
Statistical analysis All data from the first and fifth day of consecutive handling were used in the analyses. Following a two-day break from handling, data were also collected from the sixth and tenth day (see Figure  1 ). Basic descriptive statistics and correlations were calculated using Minitab 18. For the majority of analyses, Generalised Linear Mixed Models (containing both fixed and random effects) were fitted in Genstat (16th Edition) using the REML algorithm with a log link function, a Poisson error distribution and dispersion parameter fixed at one. To investigate differences in play and handling responses (USV production and hand following) in handled rats between cohorts the fixed effects part of the model comprised treatment, cohort, day, treatment X cohort x day interaction effects.