dataesr/scientific-paragraphs-categorization huggingface dataset:
In case no individuals were measured, we used the mean value from the literature (see open access data for specific values and references  53  ). Anti-predation strategy was assessed by estimating escape distance of the incubating bird when a human approached the nest, because species that are cryptic typically stay on the nest much longer than non-cryptic species, sometimes until nearly stepped upon  48, 54. Escape distance was obtained for all species. Forty-four authors of this paper estimated the distance (in m) for one or more species based on their own data or experience. For 10 species, we also obtained estimates from the literature  48. We then used the median 'estimated escape distance' for each species. In addition, for 13 species we obtained 'true escape distance'. Here, the researcher approached a nest (of known position) and either estimated his distance to the nest or marked his position with GPS when the incubating individual left the nest.
Statistical analyses. Unless specified otherwise, all analyses were performed on the nest level using median bout length and extracted period length. We used phylogenetically informed comparative analyses to assess how evolutionary history constrains the incubation rhythms (estimated by Pagel's λ coefficient of phylogenetic signal  55, 56  ) and to control for potential non-independence among species due to common ancestry. This method explicitly models how the covariance between species declines as they become more distantly related  55, 57, 58. We used the Hackett  59  backbone phylogenetic trees available at http://birdtree. org  60  , which included all but one species (Charadrius nivosus) from our dataset. Following a subsequent taxonomic split  61  , we added Charadrius nivosus to these trees as a sister taxon of Charadrius alexandrinus.
Phylogenetic uncertainty was accounted for by fitting each model with 100 phylogenetic trees randomly sampled from 10,000 phylogenies at http://birdtree. org  60. The analyses were performed with Bayesian phylogenetic mixed-effect models (Fig. 4  and Extended Data Table  2  and 4 ) and the models were run with the 'MCMCglmm' function from the R package 'MCMCglmm'  62. In all models, we also accounted for multiple sampling within species and breeding site (included as random effects). In models with a Gaussian response variable, an inverse-gamma prior with shape and scale equal to 0. 001 was used for the residual variance (i. e. variance set to one and the degree of belief parameter to 0. 002). In models with binary response variables, the residual variance was fixed to one. For all other variance components the parameter-expanded priors were used to give scaled F-distributions with numerator and denominator degrees of freedom set to one and a scale parameter of 1,000.
Model outcomes were insensitive to prior parameterization. The MCMC chains ran for 2,753,000 iterations with a burn-in of 3,000 and a thinning interval of 2,500. Each model generated ~1,100 independent samples of model parameters (Extended Data Table  2  and 4 ). Independence of samples in the Markov chain was assessed by tests for autocorrelation between samples and by using graphic diagnostics. First, we used MCMCglmm to estimate Pagel's λ (phylogenetic signal) for bout and period length (Gaussian), and to show that our estimates of these two incubation variables were independent of how often the incubation behaviour was sampled ('sampling' in min, ln-transformed; Extended Data Table  2 ). Hence, in subsequent models, sampling was not included. Then, we used MCMCglmm to model variation in bout length and period length.
Acknowledgements We thank all that made the data collection possible. We are grateful to  W. Schwartz ,  E. Schlicht ,  W. Forstmeier ,  M. Baldwin ,  H. Fried Petersen ,  D. Starr-Glass , and  B. Bulla  for comments on the manuscript and to  F. Korner-Nievergelt ,  J. D. Hadfield ,  L. Z. Garamszegi ,  S. Nakagawa ,  T. Roth ,  N. Dochtermann ,  Y. Araya ,  E. Miller  and  H. Schielzeth  for advice on data analysis. Data collection was supported by various institutions and people listed in the Supplementary Data 1: https://osf. io/sq8gk16. The study was supported by the  Max Planck Society  (to B. K. ). M. B. is a PhD student in the  International Max Planck Research School for Organismal Biology.
recruitment and training of the participating gPs Ten volunteer GPs working in the suburbs west of Paris were trained by two pneumologists during two 3-hour continuing education sessions. During the first session, the study protocol was explained and the GPs received theoretical and practical training in spirometry and were provided with a portable spirometer (Spirodoc ® coupled to WinspiroPRO ® software; MIR, Langlade, France). This instrument allows direct visualization of the flow-volume curve and the expiration time. A beep is emitted after 6 seconds of expiration. The GPs were asked to come to a second session with five test results to pursue their training. Before and after the sessions, a 12-question questionnaire evaluating each participant's knowledge of spirometry, its acceptability and reproducibility criteria, and the diagnostic criterion of AO was completed and graded on 100 points.
Acknowledgments The authors thank  Drs Yves Bertin ,  Julien Uzzan ,  Michel Courteaud ,  Robert Lestrat ,  Marie-Laure Megret-Gabeaud ,  Pierre Sebbag ,  Linda Terrasse ,  Didier Gérard , and  Christian Weiss  for their participation in the study,  Drs Elise Nedelec  and  Sébastien Tubiana  for their participation in the design of the study and collection of data, and  CARDIF  for its grant.
ACKNOWLEDGEMENTS We thank  DE. Emmanuel Ibarboure  (LCPO),  DE. Patrick Garrigue (ENSCBP) , and  Pr. Neso Sojic  ( ENSCBP ) for assistance with  AFM, DE. Nicolas Guidolin (LCPO)  for assistance with MALLS, and  Dr. Sandra Ormenese  (Imaging and flow cytometry platform -GIGA-R) for her help with confocal laser scanning microscopy.
To search the NMP region for genes known to be involved in sex determination / differentiation in other taxa, we analysed the 283 non annotated protein sequences that where located in the NMP region. Of these, 184 returned a BLAST result, but 39 were described as hypothetical proteins in the D. pulex draft transcriptome DAPPUDRAFT and did not reliably match any proteins in the NCBI non-redundant protein database. Among the remaining 145 successfully annotated sequences, 121 (82%) had a top hit on D. pulex or D. magna sequences, while the others matched various arthropods (15 sequences), and other invertebrates (ten sequences). We compared the 145 annotated genes with the NCBI list of 601 genes known to be involved in sex determination or sex differentiation in other invertebrates, and identified 14 candidate genes (Table  3 ).
037 between Yakutsk and Moscow, 0. 041 between Yakutsk and Volgograd, and 0. 010 between Moscow and Volgograd;  Galimov et al. 2011 ; Genbank accession number JF750770. 1 for Moscow, AY803073. 1 for Volvograd, and [added upon acceptance] for Yakutsk). Microsatellite markers distributed across the genome were used to investigate the parental lines. Markers that were heterozygous in the NMP mother and for which father and mother had different genotypes were selected and genotyped in the offspring. For all these markers, it could unambiguously be determined which of two maternal alleles was transmitted to a given offspring. Hence, linkage of markers to the NMP-determining region could be assessed, by assaying co-transmission of maternal alleles with the phenotype (i. e. with the W vs. Z chromosome).
Samples were genotyped using ABI 3730 capillary sequencer and GENEMAPPER software v. 3. 0 (Applied Biosystems). A total of 81 microsatellite loci (see Supplementary Material S1) were tested in the parents. Of these, 60 were polymorphic in one or both parents and thus genotyped in the offspring (47 in NMPxMP_1 and 21 in NMPxMP_2, partially overlapping). Linkage to the NMP phenotype was assessed with a Fisher's Exact tests (two-tailed). Some of the markers were specifically designed in regions for which linkage to the NMP phenotype was suspected based on information from an earlier version of the genetic map  (Routtu et al. 2010; Routtu et al. 2014 ) and the initial finding of weak but significant linkage of one marker (dm_scf00243_208642) in the NMPxMP_1 cross. Therefore, the markers do not represent a random sample throughout the genome.
magna genome v2. 4 (bioproject reference PRJNA298946, on the NCBI repository: https://www. ncbi. nlm. nih. gov/bioproject/?term=PRJNA298946) that had been mapped to LG3. Markers that had more than one third of missing genotypes (amplification failures, etc. ) were discarded. The mapping procedure consisted in first positioning and ordering the markers according to previously available data  (Dukič et al. in press) , if possible, and secondly by estimating genetic distances among the ordered markers according to standard procedures. Specifically, we ordered our markers by using the cM position of the nearest mapped SNP from the same scaffold in the reference genetic map v4. 0. 1. Microsatellite markers on scaffolds that were not mapped in the reference genetic map were positioned according to the estimated recombination fraction in our crosses between these markers and already mapped markers.
Linkage disequilibrium for all individuals (i. e. , including NMP) was then estimated via pairwise r 2 for each pair of SNPs (see Supplementary Material S7), using the program MCLD  (Zaykin et al. 2008). Significance was tested using 9999 permutations, and the extent of LD was visualized using a heatmap constructed in R using the LDheatmap package  (Shin et al. 2006 ). To test for signatures of historical recombination between W and Z haplotypes, we used a filtered dataset composed of 140 polymorphic sites in the region, retaining just one site per read (a maximum of two polymorphic sites on the same read were present in the whole data set, but SNPs on the same read were always in full linkage). We then phased these data using the GERBIL program implemented in the package GEVALT V2. 0  (Davidovich et al.
SNP effect and identification of candidate genes involved in sex determination To assess whether the NMP region contains candidate genes with known functions related to sex differentiation or sex determination, we extracted all 1306 protein sequences corresponding to transcript sequences located on the scaffolds in the NMP region, and reduced isoform redundancy using BlastClust (http://toolkit. tuebingen. mpg. de/blastclust) with the following parameters: minimum length coverage of 60%, minimum identity of 90%, minimum transcript size of 100 amino acids. This resulted in a set of 361 protein sequences, which we trimmed by hand to remove further the redundancy (we only kept one transcript for each gene). The retained 283 protein sequences (see Supplementary Material S9 for the complete list) were blasted against the NCBI nr database with Blast2GO  (Conesa and Götz 2008) , using blastp and a maximum e-value of 10 -10.
Annotated genes were then compared with a list of 601 genes obtained from the NCBI gene data base using the keywords "sex determination" and "sex differentiation". We also used the GFF file (also available on NCBI, bioproject reference PRJNA298946), which contains gene features of D. magna, to classify each SNP in the NMP region according to whether it induces a synonymous or a non-synonymous change. This analysis was done using the software tool IGV  (Robinson et al. 2011). Tables  Table 1. Comparison between crosses with one parent heterozygous (NMP x MP) and both parents homozygous for the MP factor. The table shows Fisher's Exact Test P-values for all pairs of markers studied in (a) the NMPxMP_1 cross and (b) the NMPxMP_2 cross. (Sephadex "Small" by Sigma Aldrich: 50 µm diameter) at a concentration to 0.
end 100 cycle sequencing by the Quantitative Genomics Facility service of the Department of Biosystem Science and Engineering (D-BSSE, ETH), Basel, Switzerland. The quality of the raw sequencing reads (library-wide and per-base) was assessed with FastQC (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/), and reads were checked for barcode integrity, absence of adapter sequences within the reads, and integrity of the PstI cut site. The reads were sorted individually by barcode and filtered to remove reads with uncalled bases and an overall base quality score of less than 24. Reads were subsequently aligned to the Daphnia magna genome (V2. 4; Daphnia Genomic Consortium, bioproject reference PRJNA298946, on the NCBI repository: https://www. ncbi. nlm. nih. gov/bioproject/?term=PRJNA298946) using BWA v.
Acknowledgements We thank the  Zoo of Moscow  and  N. I. Skuratov  for sampling permits, and  David Frey  for help with culture maintenance indoors. We thank the  Department of Biosystem Science and Engineering of the ETH Zurich , in particular  C. Beisel  and  I. Nissen  for Illumina sequencing, and we gratefully acknowledge support by  M-P. Dubois , the platform  Service des Marqueurs Génétiques en Ecologie at CEFE , and the genotyping and sequencing facilities of the  Institut des Sciences de l'Evolution-Montpellier  and the  Labex Centre Méditerranéen Environnement Biodiversité (CeMEB). We thank  M. Roesti  for the modified RAD-seq protocol and for the discussions and scripts on the linkage disequilibrium analysis. We thank the  University of Fribourg , the  Montpellier Bioinformatic Biodiversity plateform  and the  Labex CeMEB  for access to high-performance computing clusters.
Data collection and analysis: The database consisted of 2638 written responses given by the GPs to an open-ended question asking for the reasons why drug treatment was not changed as suggested by the national guidelines. All answers were coded using constant comparison analysis. A matrix analysis of codes per GP allowed the construction of a response typology, where types were defined by codes as attributes. Initial coding and definition of types were performed independently by two teams. Results: Initial coding resulted in a list of 69 codes in the final codebook, representing 4764 coded references in the question responses. A typology including seven types was constructed. 100 GPs were allocated to one and only one of these types, while 25 GPs did not provide enough data to allow classification.
Coding All the responses were entered into a database and coded using a constant comparison process without predetermined categories. This generated an initial list of codes. The initial coding was performed independently by two teams of researchers ( JPL/VY and IAA/AM) using a qualitative analysis software package (NVivo 9. 2, QSR International Pty Ltd, Doncaster, Australia; 2011). The two lists were then combined into one final codebook. Discrepancies were resolved by discussion, and remaining disagreements went to arbitration with a fifth researcher ( JSC).
Typology Applying the attributes to the whole database allowed the classification to one of the seven response types for 100 of the 125 GPs. The 25 remaining did not have enough data to allow a classification using attributes (figure  1 ). For the 100 GPs allocated to a type, the mean number of patient was 8. 0 (range 2-18). The 'optimists' was the largest group (28 GPs). Great expectations related to the patient's recent or expected lifestyle changes were their central characteristics: 'Repeating the lifestyle recommendations should be enough to reach the HbA1c target'. Three GPs had a 'negotiator' tendency, but the negotiations were mostly focused on lifestyle too: 'We insisted again on diet and exercise'. Follow-up visits for re-evaluations were often scheduled. Twenty GPs were classified as 'negotiators'.
Detailed findings and comparison with existing literature Defining a typology regarding the reasons provided for not initiating or increasing the treatment of a cardiovascular risk factor when indicated has not been done previously. The survey study of Oliveria et al 32 did ask the physician the reasons of the decision for a given patient, but it was not conducted in a framework where the physician was specifically urged to give guideline-based care. While our results cannot be confronted with previous results of the exact same nature, the various factors and behaviours involved in the inaction process have all been described before. Reviewing the whole database for a first impression, the overwhelming confidence in lifestyle counselling is The number of references for a given code represents the number of sections of the initial verbatim allocated to that particular code.
1D ). As demonstrated by RPA and RACE analyses, the lengths (Supplemental Fig. S1D-F ) and sequences (data not shown) of Cirbp mRNA 5 ′ and 3 ′ regions were indistinguishable at different temperatures. Temperature-dependent Cirbp mRNA accumulation is regulated by a post-transcriptional mechanism Since Cirbp pre-mRNA levels were found to be rather constant at different temperatures, we considered that Cirbp transcription might also be temperature-independent. To test this hypothesis, we performed a chromatin immunoprecipitation (ChIP) assay with an antibody directed against RNA polymerase II subunit b (POLR2B). Specifically, we quantified the levels of immunoprecipitated DNA fragments encompassing the Cirbp promoter or gene body regions in cells incubated for 6 h at 33°C or 38°C by quantitative real-time PCR (RT-qPCR).
RBPDB (the database of RNA-binding protein specificities, version 1. 3 release; http://rbpdb. ccbr. utoronto. ca) was used for scanning the Cirbp sequence for potential RBP-binding sites. The search for splice sites and cis-acting elements was performed on the RegRNA 2. 0  (Chang et al. 2013 ) and the ASSP  (Wang and Marin 2006)  Web servers. Gene ontology analysis was performed using DAVID Bioinformatics resources 6. 8 analysis Web server (https://david-d. ncifcrf. gov). RNA isolation and quantification, ChIP, and bioluminescence reporter assays were performed according to standard methods described in detail in the Supplemental Material.
RNA-seq and data analysis DNase I-treated total RNA samples were ribo-depleted using the Ribo-Zero Gold rRNA removal kit (Illumina). Paired-end, strand-specific cDNA libraries of 50-bp inserts were prepared according to an in-house protocol of the iGE3 genomics platform and sequenced using the Illumina HiSeq2500 platform. Detailed information on data analysis and mathematical modeling is in the Supplemental Material. Data have been deposited to the Gene Expression Omnibus repository under accession number GSE85553.
Acknowledgments We thank  Minoru Yoshida  ( RIKEN, Institute of Physical and Chemical Research, Saitama, Japan ) for the generous gift of SSA, and  M. Koksharov  and  N. Ugarova  ( University of Moscow, Russia ) for the Luciola mingrelica luciferase mutant. We are extremely grateful to  André Liani ,  Yves-Alain Poget , and  Georges Severi  ( Mechanical Workshop Unit of the Department of Molecular Biology, University of Geneva ) for designing and engineering the homemade incubators with electronic temperature controls. We also express our gratitude to  Mylène Docquier  and her collaborators ( Genomics Platform, University of Geneva ) for RNA-seq, and  Nicolas Roggli  ( Department of Molecular Biology, University of Geneva ) for the artwork. The computations were performed on the  Vital-IT  (http://www.
8%-52. 7%, which likely reflects the different biases in gene selection criteria between centres and specific consortium arrangements for lethal gene characterization (TCP and UCD) (Extended Data Fig. 2A, B ). No significant bias is observed in the distribution of lethal genes across mouse chromosomes (Extended Data Fig. 2C, D ). Overall, however, the lethal proportion (23. 4%) is consistent with published observations of null alleles  7, 9, 12, 13  , particularly when combined with subviable lines (11. 3%), resulting in 65. 3% viability for IMPC KO lines overall. A main goal of this project is to provide phenotype data for unknown or novel genes, i. e. those with no prior report of a targeted null allele in the mouse (curated in Mouse Genome Informatics). The primary viability data indicated that such unannotated genes displayed an overall viability rate of 66.
5%, compared to the 62% viability rate among previously reported null alleles (Extended Data Fig. 2E ; novel versus prior gene lists in Supplementary Table  3 ; list of all first publications or reports of gene knockouts in Supplementary Table  4 ). These data reveal consistent identification of essential genes in our program, and further support that approximately 35% (24% lethal and 11% subviable) of null mutations across the genome are essential for survival at normal Mendelian ratios. Functional data from mouse knockouts are highly informative, and thus would be predicted to have a strong impact on Gene Ontology (GO) Consortium 14 annotations. For the 1,751 IMPC mouse lines phenotyped to date, IMPC phenotyping provides the only experimental evidence for over 40% of the genes in our dataset.
Using the GO Slim tool, which clusters terms associated with each gene into a set of broad categories, we observed enrichment in lethal and subviable genes within several categories (Extended Data Fig. 3 ). Compared to novel genes, the number of annotations for a majority Process and Function categories was greater for published alleles, highlighting the value of our analysis in assigning function to novel, previously uncharacterized genes. We used data from three recent publications on genome-wide screens for cell-essential genes in human cells to address the overlap between essential genes in the human and mouse genome  [15] [16] [17]. We selected core essential genes from each study and compared to human orthologs of mouse essential genes on the consensus list of curated IMPC-MGI genes.
The catalogue of KO lines and all phenotype data are available to the community via the IMPC portal (www. mousephenotype. org), with an embryo phenotyping-specific portal at www. mousephenotype. org/data/embryo (a guide to accessing, viewing and using these data is available on the IMPC portal at http://www. mousephenotype. org/data/documentation/docexplore) Using a tiered strategy, we established clear viable vs. lethal (defined if homozygous embryos were absent or lacked a heartbeat) calls at up to four different time points for a total of 283 lethal lines (A comprehensive progress table for all 1861 alleles is provided in Supplementary Table  5 ), the total number varying by progress through the pipeline. From these data, we established windows of lethality for 242 genes with complete data to more precisely define the timing of embryo death.
5 embryos revealed abnormal development of the kidney pelvis (Fig. 2i, l ), severely hypoplastic lungs and a thin myocardium (Fig  2j, m ). Homozygous Klhdc2 embryos at E14. 5 displayed hindlimb preaxial polydactyly (Fig. 2n ,q arrow) and edema (Fig. 2n ,q arrowhead). Sections of micro-CT volumes additionally revealed hypoplastic adrenals (Fig. 2s ), displaced kidneys, a shorter tongue, and abnormal intestines (Fig  2r ). As stated above, a number of mutants with impaired cardiovascular function were identified (Fig. 2a-c ), including Strn3, Atg3, and Slc39a8 (Extended Data Fig. 5 ). Similarly, cardiovascular defects were common at E9. 5, illustrated in detail using OPT (e. g. , Tmem100, Extended Data Fig. 6 ). OPT datasets can be manipulated in three dimensions to reveal additional phenotypes such as abnormal neural tube closure, turning and chorionallantois fusion seen in homozygous Gfpt mutant embryos (Fig.