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119 results for “missing data”
Data from: Out-of-sample predictions from plant–insect food webs: robustness to missing and erroneous trophic interaction records
With increasing biotic introductions, there is a great need for predictive tools to anticipate which new trophic interactions will develop and which will not. Phylogenetic constraint of interactions in both native and novel food webs can make some novel interactions predictable. However, many food webs are sparsely sampled, or may include inaccurate interactions. In such cases, it is unclear whether modeling methods are still useful to anticipate novel interactions. We ran bootstrap simulations of host-use models on a Lepidoptera–plant data set to remove native trophic records or add erroneous records in order to observe the effect of missing or erroneous data on the prediction of interactions with novel plants. We found that the model was robust to a large amount of missing interaction records, but lost predictive power with the addition of relatively few erroneous interaction records. The loss of predictive power with missing records was due to inaccuracy in estimating phylogenetic distance between native and novel hosts. Removal of interaction records proportionally to their encounter frequency in the field had little effect on the loss of predictive power. Host-use models may have immediate value for predicting novel interactions from large, but sparsely sampled databases of trophic interactions.
Data from: Phenotypic selection favors missing trait combinations in coexisting annual plants
Trade-offs among traits are important for maintaining biodiversity, but the role of natural selection in their construction is not often known. It is possible that trade-offs reflect fundamental constraints, negative correlational selection, or directional selection operating on costly, redundant traits. In a Sonoran Desert community of winter annual plants, we have identified a trade-off between relative growth rate and water-use efficiency among species, such that species with high relative growth rate have low water-use efficiency and vice versa. We measured selection on water-use efficiency, relative growth rate, and underlying traits within populations of four species at two study sites with different average climates. Phenotypic trait correlations within species did not match the among-species trade-off. In fact, for two species with high water-use efficiency, individuals with high relative growth rate also had high water-use efficiency. All populations experienced positive directional selection for water-use efficiency and relative growth rate. Selection tended to be stronger on water-use efficiency at the warmer and drier site, and selection on relative growth rate tended to be stronger at the cooler and wetter site. Our results indicate that directional natural selection favors a phenotype not observed among species in the community, suggesting that the among-species trade-off could be due to pervasive genetic constraints, perhaps acting in concert with processes of community assembly.
Data from: Determinants of maternal near misses in Morocco: too late, too far, too sloppy?
Background: In Morocco, there is little information on the circumstances surrounding maternal near misses. This study aimed to determine the incidence, characteristics, and determinants of maternal near misses in Morocco. Method:A prospective case-control study was conducted at 3 referral maternity hospitals in the Marrakech region of Morocco between February and July 2012. Near-miss cases included severe hemorrhage, hypertensive disorders, and prolonged obstructed labor. Three unmatched controls were selected for each near-miss case. Three categories of risk factors (sociodemographics, reproductive history, and delays), as well as perinatal outcomes, were assessed, and bivariate and multivariate analyses of the determinants were performed. A sample of 30 near misses and 30 non-near misses was interviewed. Results:The incidence of near misses was 12‰ of births. Hypertensive disorders during pregnancy (45%) and severe hemorrhage (39%) were the most frequent direct causes of near miss. The main risk factors were illiteracy [OR = 2.35; 95% CI: (1.07–5.15)], lack of antenatal care [OR = 3.97; 95% CI: (1.42–11.09)], complications during pregnancy [OR = 2.81; 95% CI:(1.26–6.29)], and having experienced a first phase delay [OR = 8.71; 95% CI: (3.97–19.12)] and a first phase of third delay [OR = 4.03; 95% CI: (1.75–9.25)]. The main reasons for the first delay were lack of a family authority figure who could make a decision, lack of sufficient financial resources, lack of a vehicle, and fear of health facilities. The majority of near misses demonstrated a third delay with many referrals. The women's perceptions of the quality of their care highlighted the importance of information, good communication, and attitude. Conclusion:Women and newborns with serious obstetric complications have a greater chance of successful outcomes if they are immediately directed to a functioning referral hospital and if the providers are responsive.
Data from: Missing the people for the trees: identifying coupled natural-human system feedbacks driving the ecology of Lyme disease
1. Infectious diseases are rapidly emerging and many are increasing in incidence across the globe. Processes of land-use change, notably habitat loss and fragmentation, have been widely implicated in emergence and spread of zoonoses such as Lyme disease, yet evidence remains equivocal. 2. Here we discuss and apply an innovative approach from the social sciences, instrumental variables, that seeks to tease out causality from observational data. Using this approach, we revisit the effect of forest fragmentation on Lyme disease incidence, focusing on human interaction with fragmented landscapes. Though human interaction with infected ticks is of clear and fundamental importance to human disease incidence, human activities that influence exposure have been nearly universally overlooked in the ecology literature. 3. Using county-level land-use and Lyme disease incidence data for ~800 counties from the northeastern United States over the span of a decade, we illustrate (1) human interaction with fragmented forest landscapes reliably predicts Lyme disease incidence, while ecological measures of forest fragmentation alone are unreliable predictors and (2) that identifying the effect of forest fragmentation on human disease requires addressing the feedback between Lyme disease risk and human decisions to avoid interaction with high-risk landscapes. 4. Synthesis and applications. The innovative approach and novel results help to clarify the equivocal literature on forest fragmentation and Lyme disease, and illustrate the key role that human behavior may be playing in the ecology of Lyme disease in North America. Accounting for human activity and behavior in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease, as well as actionable intervention strategies to reduce disease burden in a changing world. For example, our model results have practical implications for land-use policy aimed at disease reduction. Our model suggests land use regulations that reduce parcel size would be an actionable approach for policy makers concerned about increasing Lyme disease incidence in the northeastern US.10-Oct-2018
Data from: RADcap: sequence capture of dual-digest RADseq libraries with identifiable duplicates and reduced missing data
Molecular ecologists seek to genotype hundreds to thousands of loci from hundreds to thousands of individuals at minimal cost per sample. Current methods, such as restriction site associated DNA sequencing (RADseq) and sequence capture, are constrained by costs associated with inefficient use of sequencing data and sample preparation. Here, we introduce RADcap, an approach that combines the major benefits of RADseq (low cost with specific start positions) with those of sequence capture (repeatable sequencing of specific loci) to significantly increase efficiency and reduce costs relative to current approaches. RADcap uses a new version of dual-digest RADseq (3RAD) to identify candidate SNP loci for capture bait design, and subsequently uses custom sequence capture baits to consistently enrich candidate SNP loci across many individuals. We combined this approach with a new library preparation method for identifying and removing PCR duplicates from 3RAD libraries, which allows researchers to process RADseq data using traditional pipelines, and we tested the RADcap method by genotyping sets of 96 to 384 Wisteria plants. Our results demonstrate that our RADcap method: (1) methodologically reduces (to <5%) and allows computational removal of PCR duplicate reads from data; (2) achieves 80-90% reads-on-target in 11 of 12 enrichments; (3) returns consistent coverage (≥4x) across >90% of individuals at up to 99.8% of the targeted loci; (4) produces consistently high occupancy matrices of genotypes across hundreds of individuals; and (5) costs significantly less than current approaches.
Data from: Nest inheritance is the missing source of direct fitness in a primitively eusocial insect
Animals that co-operate with non-relatives represent a challenge to inclusive fitness theory, unless co-operative behavior is shown to provide direct fitness benefits. Inheritance of breeding resources could provide such benefits, but this route to co-operation has been little investigated in the social insects. We show that nest inheritance can explain the presence of unrelated helpers in a classic social insect model, the primitively eusocial wasp Polistes dominulus. We found that subordinate helpers produced more direct offspring than lone breeders, some while still subordinate but most after inheriting the dominant position. Thus, while indirect fitness obtained through helping relatives has been the dominant paradigm for understanding eusociality in insects, direct fitness is vital to explain co-operation in P. dominulus.
Data from: Missed opportunities for HIV testing among patients newly presenting for HIV care at a Swiss university hospital: a retrospective analysis
Objectives: To determine the frequency of missed opportunities (MOs) among patients newly-diagnosed with HIV, risk factors for presenting MOs, and the association between MOs and late presentation to care. Design: Retrospective analysis Setting: HIV outpatient clinic at a Swiss tertiary hospital Participants: Patients aged ≥18 years old newly presenting for HIV care between 2010 and 2015 Measures: Number of medical visits, up to five years preceding HIV diagnosis, at which HIV testing had been indicated, according to Swiss HIV testing recommendations. A visit at which testing was indicated but not performed was considered a MO for HIV testing. Results: Complete records were available for all 201 new patients of whom 51% were male and 33% from sub-Saharan Africa. Thirty patients (15%) presented with acute HIV infection while 119 patients (59%) were late presenters (LPs) (CD4 counts <350 cells/mm3 at diagnosis). Ninety-four patients (47%) had presented at least one MO, of whom 44 (47%) had multiple MOs. MOs were more frequent among individuals from sub-Saharan Africa, men who have sex with men, and patients under follow-up for chronic disease. MOs were less frequent in LPs than non-LPs (42.5% versus 57.5%, P = 0.03). Conclusions: At our centre, 47% of patients presented at least one MO. Whilst our late presentation rate is higher than the national figure of 49.8%, LPs were less likely to experience MOs, suggesting that these patients were diagnosed late through presenting late, rather than through being failed by our hospital. We conclude that, in addition to optimising physician-initiated testing, access to testing must be improved among patients unaware they are at HIV risk and who do not seek health care.
Data and code for "Superconducting switching jump induced missing first Shapiro step in Al-InSb nanosheet Josephson junctions"
<p><strong>Brief description</strong></p> <p>This repository contains data, code, and other materials for "Superconducting switching jump induced missing first Shapiro step in Al-InSb nanosheet Josephson junctions" (arXiv:2403.07370). </p> <p><strong>Data formats</strong></p> <ul> <li>DAT: Plain-text tabular data.<br>DAT files can be visualized by Spyview, qtplot (a portable version for Windows can be downloaded <a href="https://github.com/cover-me/qtplot/releases/download/2020.09.21/qt_plot.2020.09.21.7z">here</a>), Jupyter notebooks in ZIP files or <a href="https://github.com/cover-me/qtview">here</a>.</li> <li>SET: Instrument settings.</li> <li>PY: Measurement scripts.</li> <li>IPYNB or HTML: Jupyter notebooks with code and figures. IPYNB can be previewed on this <a href="https://kokes.github.io/nbviewer.js/viewer.html">page</a>.</li> </ul>
Missing data in sea turtle population monitoring: a Bayesian statistical framework accounting for incomplete sampling
<p>Monitoring how populations respond to sustained conservation measures is essential to detect changes in their population status and determine the effectiveness of any interventions. In the case of sea turtles, their populations are difficult to assess because of their complicated life histories. Ground-derived clutch counts are most often used as an index of population size for sea turtles; however, data are often incomplete with varying sampling intensity within and among sites and seasons. To address these issues, we: (1) develop a Bayesian statistical modelling framework that can be used to account for sampling uncertainties in a robust probabilistic manner within a given site and season; and (2) apply this to a previously unpublished long-term sea turtle dataset (n = 17 years) collated for the Republic of the Congo, which hosts two sympatrically nesting species of sea turtle (leatherback turtle [<em>Dermochelys coriacea</em>] and olive ridley turtle [<em>Lepidochelys olivacea</em>]). The results of this analysis suggest that leatherback turtle nesting levels dropped initially and then settled into quasi-cyclical levels of interannual variability, with an average of 573 (mean, 95% prediction interval: 554–626) clutches laid annually between 2012 and 2017. In contrast, nesting abundance for olive ridley turtles has increased more recently, with an average of 1,087 (mean, 95% prediction interval: 1,057–1,153) clutches laid annually between 2012 and 2017. These findings highlight the regional and global importance of this rookery with the Republic of the Congo, hosting the second largest documented populations of olive ridley and the third largest for leatherback turtles in Central Africa; and the fourth largest non-arribada olive ridley rookery globally. Furthermore, whilst the results show that Congo's single marine and coastal national park provides protection for over half of sea turtle clutches laid in the country, there is scope for further protection along the coast. Although large parts of the African coastline remain to be adequately monitored, the modelling approach used here will be invaluable to inform future status assessments for sea turtles given that most datasets are temporally and spatially fragmented. </p>
Comparison of missing data handling methods for variant pathogenicity predictors
<p>This upload contains result files from executing all experiments described in the manuscript.</p>
Data from: Resolving the mesoscopic missing link: biophysical modeling of EEG from cortical columns in primates
<p class="MsoNormal"><span>Event-related potentials (ERP) are among the most widely measured indices for studying human <span>cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires <em>in vivo</em> measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach <em>in vivo</em> to clarify the source of a representative cognitive ERP component. To that end, </span>LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. <span>We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach </span>represents an important bridge between laminar microcircuitry, through the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp. </span></p>
Missing data of Patient F for Chaudhary et al 2017 PloS Biology Publication
<p>The folder contains the missing data set of patient F for Chaudhary et al 2017 PloS Biology Publication</p>
Effects of missing data and data type on phylotranscriptomic analysis of stony corals (Cnidaria: Anthozoa: Scleractinia)
<p>BLASTn summary</p> <p>Phylogenetic data matrices and trees</p>
Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales - ALL 2011 & 2014 AUDIO DATA
<p><strong>Description of the data and file structure<br></strong>This record contains all 2011 & 2014 audio data from animal-borne biologging instruments (Dtags) temporarily affixed to fish-eating killer whales, supporting the analyses presented in the following article:</p> <p> Tennessen. J.B., Holt, M.M., Wright, B.M., Hanson, M.B., Emmons, C.K., Giles, D.A., Hogan, J.T., Thornton, S.J., Deecke, V.B. 2024. Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales. <em>Global Change Biology</em>.<strong> </strong>In press.</p> <p>The data include the following: the 2011 & 2014 audio files from analyzed Dtag depoyments. All methodological details necessary to contextualize analysis procedures are provided in the methods section of the article. The following data files are available under separate DOIs: 10.5281/zenodo.13333019 - all 2009 & 2010 audio data; 10.5281/zenodo.13308835 - (1) all calibrated movement data from analyzed Dtag deployments, and (2) a spreadsheet containing the variables included in the fully-saturated and final models listed in Table 2 in the article cited above.</p> <p>These data are provided by NOAA Fisheries' Northwest Fisheries Science Center, and Fisheries and Oceans Canada, to support reproducibility of all statistical analyses presented in the article. Please cite your usage of our data. For inquiries about data use, or for general questions, please contact Dr. Jennifer B. Tennessen, at jtenness@uw.edu.</p> <p> </p> <p><strong>Description of audio data files</strong><br>The data files contain the .dtg extension. This is the compressed raw data from all analyzed deployments. Once files are downloaded, they will need to be decompressed, which is done using the tagtools tool kit for Matlab, R or Octave, available at https://github.com/animaltags .</p> <p>Each deployment is named using the first letter of the genus and species name ("oo" for Orcinus orca), followed by the two-digit year (e.g., 09 for 2009), followed by the 3-digit Julian day (e.g., 246), followed by a letter denoting the population (a-d for Northern Residents, m for Southern Residents), followed by a series of numbers that denote the specific block (on the tag memory board) from which the data came. All files from a deployment should be put within a folder for that deployment, so that the functions within the tagtools tool kit can locate them.</p> <p>Once the .dtg files are decompressed, there will be 4 new files for every decompressed file, with extensions as follows: .wav (audio) as well as .pk, .swv, .txt. The audio files are ready to use in .wav form, and can be viewed using any audio software. We recommend using Matlab with the tagtools tool kit, or viewing the files in batch mode within RavenPro (https://store.birds.cornell.edu/collections/raven-sound-software).</p> <p>We provide calibrated movement data (see DOI: 10.5281/zenodo.13308835). However, if users wish to run their own calibration from raw movement data, the .swv files are used for this purpose along with the tagtools tool kit in Matlab, R or Octave, available at https://github.com/animaltags .</p>
Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales - ALL 2009 & 2010 AUDIO DATA
<p><strong>Description of the data and file structure<br></strong>This record contains all 2009 & 2010 audio data from animal-borne biologging instruments (Dtags) temporarily affixed to fish-eating killer whales, supporting the analyses presented in the following article:</p> <p> Tennessen. J.B., Holt, M.M., Wright, B.M., Hanson, M.B., Emmons, C.K., Giles, D.A., Hogan, J.T., Thornton, S.J., Deecke, V.B. 2024. Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales. <em>Global Change Biology</em>.<strong> </strong>In press.</p> <p>The data include the following: the 2009 & 2010 audio files from analyzed Dtag depoyments. All methodological details necessary to contextualize analysis procedures are provided in the methods section of the article. The following data files are available under separate DOIs: 10.5281/zenodo.13328931 - all 2011 & 2014 audio data; 10.5281/zenodo.13308835 - (1) all calibrated movement data from analyzed Dtag deployments, and (2) a spreadsheet containing the variables included in the fully-saturated and final models listed in Table 2 in the article cited above.</p> <p>These data are provided by NOAA Fisheries' Northwest Fisheries Science Center, and Fisheries and Oceans Canada, to support reproducibility of all statistical analyses presented in the article. Please cite your usage of our data. For inquiries about data use, or for general questions, please contact Dr. Jennifer B. Tennessen, at jtenness@uw.edu.</p> <p> </p> <p><strong>Description of audio data files</strong><br>The data files contain the .dtg extension. This is the compressed raw data from all analyzed deployments. Once files are downloaded, they will need to be decompressed, which is done using the tagtools tool kit for Matlab, R or Octave, available at https://github.com/animaltags .</p> <p>Each deployment is named using the first letter of the genus and species name ("oo" for Orcinus orca), followed by the two-digit year (e.g., 09 for 2009), followed by the 3-digit Julian day (e.g., 246), followed by a letter denoting the population (a-d for Northern Residents, m for Southern Residents), followed by a series of numbers that denote the specific block (on the tag memory board) from which the data came. All files from a deployment should be put within a folder for that deployment, so that the functions within the tagtools tool kit can locate them.</p> <p>Once the .dtg files are decompressed, there will be 4 new files for every decompressed file, with extensions as follows: .wav (audio) as well as .pk, .swv, .txt. The audio files are ready to use in .wav form, and can be viewed using any audio software. We recommend using Matlab with the tagtools tool kit, or viewing the files in batch mode within RavenPro (https://store.birds.cornell.edu/collections/raven-sound-software).</p> <p>We provide calibrated movement data (see DOI: 10.5281/zenodo.13308835). However, if users wish to run their own calibration from raw movement data, the .swv files are used for this purpose along with the tagtools tool kit in Matlab, R or Octave, available at https://github.com/animaltags .</p>
Data and Codes used in the study: Flickering Gamma-Ray Flashes, the Missing Link between Gamma Glows and TGFs
<p>Description is given in the uploaded pdf document: Data_codes_description.pdf</p>
Repositories for taxonomic data: Where we are and what is missing
<p>Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15–20,000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use of molecular data in species diagnosis and description. In 2018, of the 2661 papers published in specialized taxonomic journals, molecular data were widely used in mycology (94%), regularly in vertebrates (53%), but rarely in botany (15%) and entomology (10%). Images play an important role in taxonomic research on all taxa, with photographs used in >80% and drawings in 58% of the surveyed papers. The use of omics (high-throughput) approaches or 3D documentation is still rare. Improved archiving strategies for metabarcoding consensus reads, genome and transcriptome assemblies, and chemical and metabolomic data could help to mobilize the wealth of high-throughput data for alpha-taxonomy. Because long term <span>—</span> ideally perpetual <span>—</span> data storage is of particular importance for taxonomy, energy footprint reduction via less storage-demanding formats is a priority if their information content suffices for the purpose of taxonomic studies. Whereas taxonomic assignments are quasi-facts for most biological disciplines, they remain hypotheses pertaining to evolutionary relatedness of individuals for alpha-taxonomy. For this reason, an improved re-use of taxonomic data, including machine-learning-based species identification and delimitation pipelines, <span>requires a cyberspecimen approach—linking data via unique specimen identifiers, and thereby making them </span>findable, accessible, interoperable, and reusable for taxonomic research<span>. This poses both qualitative challenges to adapt the </span>existing infrastructure of data cen<span>ters to a specimen-centered concept and quantitative challenges to host </span>and connect an estimated ≤2 million images produced per year by alpha-taxonomic studies, plus many millions of images from digitization campaigns. Of the 30–40,000 taxonomists globally, many are thought to be <span>non-professionals, and capturing the data for online storage and reuse therefore requires</span> low-complexity submission workflows and cost-free repository use. E<span>xpert taxonomists are the main stakeholders able to identify and formalize the needs of the discipline</span>; their expertise is needed to implement the envisioned<span> virtual collections of cyberspecimens.</span></p>
Nonrandom missing data can bias PCA inference of population genetic structure
<p>Population genetic studies in non-model systems increasingly use next-generation sequencing to obtain more loci, but such methods also generate more missing data that may affect downstream analyses. Here we focus on the Principal Component Analysis (PCA) which has been widely used to explore and visualize population structure with mean-imputed missing data. We simulated data of different population models with various total missingness (1%, 10%, 20%) introduced either randomly or biased among individuals or populations. We found that individuals biased with missing data would be dragged away from their real population clusters to the origin of PCA plots, making them indistinguishable from true admixed individuals and potentially leading to misinterpreted population structure. We also generated empirical data of the big brown bat (<i>Eptesicus fuscus</i>) using restriction site-associated DNA sequencing (RADseq). We filtered three data sets with 19.12%, 9.87%, and 1.35% total missingness, all showing nonrandom missing data with biased individuals dragged towards the PCA origin, consistent with results from simulations. We highlight the importance of considering missing data effects on PCA in non-model systems where nonrandom missing data are common due to varying sample quality. To help detect missing data effects, we suggest to 1) plot PCA with a color gradient showing per sample missingness, 2) interpret samples close to the PCA origin with extra caution, 3) explore filtering parameters with and without the missingness-biased samples, and 4) use complementary analyses (e.g., model-based methods) to cross-validate PCA results and help interpret population structure.</p>
Data for The missing risks of climate change
<p>This repository contains the data behind the quantitative figures (figures 1, 3, and 4) in Rising, James, et al. "The missing risks of climate change." <em>Nature</em> 610.7933 (2022): 643-651. https://www.nature.com/articles/s41586-022-05243-6.</p> <p>The figures directory contains the figures (in their accepted paper form). The data directory contains CSV files with the associated data. The rows and columns are defined as follows:</p> <p> - fig1-mc.csv: Rows describe Monte Carlo draws describing the uncertainty for each scenario (SSP1-2.6 and SSP3-7.0) and outcome variable (in the "variable" column). The "run" column describes the basis for each draw of the uncertainty (e.g., model used). The "unit" column provides the units for the "value" column. The "compound" column is TRUE if the rows report compounded uncertainty, and false if the uncertainty is only from the individual analysis stage.</p> <p> - fig3-zscores.csv: Each row is a grid cell across the globe, reporting z-scores for various hazards and the population from GPW v4.0 (https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). The z-scores are calculated compared to the recent history (1980-2010) from either longer historical data from CRU TS, with the column prefix "hist.", or from SSP3-7.0 estimates from WorldClim bioclimatic variables for 2050, with the column prefix "ssp370.". Column suffixes describe various hazards: "wet" is average precipitation in the wettest month, "dry" is annual precipitation, "logwet" is as "wet" but evaluated in logs, "logdry" is as "dry" but evaluated in logs, "pcv" is precipitation seasonality (coefficient of variation), "hot" is the maximum temperature of the warmest month, and "cld" is the minimum temperature of the coldest month. "topcol" reports the column with the most extreme z-score (with the z-score in "topscore" and a label in "toplabel").</p> <p> - fig4-dmgfunc.csv: Monte Carlo draws of the uncertainty in number of people affected across 16 impacts, reported in "affected" as a fraction of the global population, for each temperature change from preindustrial, reported in "temp".</p> <p> - fig4-pdfs.csv: Monte Carlo draws of the uncertainty in the number of people affected for each of 16 impacts and four aggregates. The fraction of the global population affected in reported in "affected" for the temperature change from preindustrial reported in "temp". The impact is labeled in "name" and the aggregate category is reported in "rname".</p> <p>Additional details on the generation of these data are included in the SI of the paper.</p>
Data from: Determinants of maternal near misses in Morocco: too late, too far, too sloppy?
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.