Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
579
datasets available to search
ShareScore release 0.9.0
Dataset results
579 results for “Stratification”
ECCO Ocean Density, Stratification, and Hydrostatic Pressure - Monthly Mean 0.5 Degree (Version 4 Release 4)
This dataset contains monthly-averaged ocean density, stratification, and hydrostatic pressure interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Ocean Density, Stratification, and Hydrostatic Pressure - Daily Mean llc90 Grid (Version 4 Release 4)
This dataset provides daily-averaged ocean density, stratification, and hydrostatic pressure on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
Data for paper "Axial wind effects on stratification and longitudinal sediment transport in a convergent estuary during wet season"
<p>This is the COAWST model data used in the paper. </p>
Data from: Diabetes mellitus and prediabetes on kidney transplant waiting list- prevalence, metabolic phenotyping and risk stratification approach
Background: Despite a significant prognostic impact, little is known about disturbances in glucose metabolism among kidney transplant candidates. We assess the prevalence of diabetes mellitus (DM) and prediabetes on kidney transplant waiting list, its underlying pathophysiology and propose an approach for individual risk stratification. Methods: All patients on active kidney transplant waiting list of a large European university hospital transplant center were metabolically phenotyped. Results: Of 138 patients, 76 (55%) had disturbances in glucose metabolism. 22% of patients had known DM, 3% were newly diagnosed. 30% were detected to have prediabetes. Insulin sensitivity and -secretion indices allowed for identification of underlying pathophysiology and risk factors. Age independently affected insulin secretion, resulting in a relative risk for prediabetes of 2.95 (95%CI 1.38-4.83) with a cut-off at 48 years. Body mass index independently affected insulin sensitivity as a continuous variable. Conclusions: The prevalence of DM or prediabetes on kidney transplant waiting list is as high as 55%, with more than one third of patients previously undiagnosed. Oral glucose tolerance test is mandatory to detect all patients at risk. Metabolic phenotyping allows for differentiation of underlying pathophysiology and provides a basis for early individual risk stratification and specific intervention to improve patient and allograft outcome.
Data from: Digging the optimum pit: antlions, spirals and spontaneous stratification
Most animal traps are constructed from self-secreted silk, so antlions are rare among trap builders because they use only materials found in the environment. We show how antlions exploit the properties of the substrate to produce very effective structures in the minimum amount of time. Our modelling demonstrates how antlions (1) exploit self-stratification in granular media differentially to expose deleterious large grains at the bottom of the construction trench where they can be ejected preferentially and (2) minimize completion time by spiral rather than central digging. Both phenomena are confirmed by our experiments. Spiral digging saves time because it enables the antlion to eject material initially from the periphery of the pit where it is less likely to topple back into the centre. As a result, antlions can produce their pits — lined almost exclusively with small slippery grains to maximize powerful avalanches and hence prey capture — much more quickly than if they simply dig at the pit's centre. Our demonstration, for the first time, of an animal utilizing self-stratification in granular media exemplifies the sophistication of extended phenotypes even if they are only formed from material found in the animal's environment.
Denoising Autoencoders for Phenotype Stratification (DAPS) Sample Trained Simulated Patient Data
<p>DAPS Trained data</p>
Denoising Autoencoders for Phenotype Stratification (DAPS) Sample Trained Patient Data
<p>Data for: https://github.com/greenelab/DAPS</p>
ChatGPT Provides Inconsistent Risk-Stratification of Patients With Atraumatic Chest Pain - Dataset
<p>Dataset for analysis of the ability of ChatGPT to risk-stratify patients with atraumatic chest pain</p>
Multimodal Features Integration: Genomics and Histopathological images for colon cancer stage prediction and survival stratification
<p>File Description</p> <p>clinical_patient_coad.xls - Clinical data for colon cancer patients<br>COAD__geneExp.xls - RNA data for colon cancer patients<br>COAD__methylation_450__TSS200-TSS1500.xls - DNA methylation data for colon cancer patients<br>COAD__miRNAExp__ReadCount.xls - miRNA data for colon cancer patients<br>COAD_DX_STG1.tar.gz - Image tiles for stage 1 colon cancer patients<br>COAD_DX_STG2.tar.gz - Image tiles for stage 2 colon cancer patients<br>COAD_DX_STG3.tar.gz - Image tiles for stage 3 colon cancer patients<br>COAD_DX_STG4.tar.gz - Image tiles for stage 4 colon cancer patients</p>
Risk stratification and prognostic value of basic coagulation parameters among COVID-19 patients
<p class="MsoNormal"><strong><span>Background</span></strong><span>:<strong> </strong></span><span>COVID-19 is a viral disease caused by a new strain of coronaviru<span>s</span><span><span>.</span></span> Currently, prognosis and risk stratification of COVID-19 patients is done by the disease's clinical presentation. Therefore, identifying laboratory biomarkers for disease prognosis and risk stratification of COVID-19 patients is critical for prompt treatment. Therefore, the main objective of this study was to </span><span>assess the risk stratification and prognostic value of basic coagulation parameters and factors associated with disease severity among COVID-19 patients, Northwest Ethiopia.</span></p> <p class="MsoNormal"><strong><span>Methods</span></strong><span>:<strong> </strong></span><span>A follow-up study was conducted among conveniently recruited COVID-19 patients attended from March to June 2021. Socio-demographic and clinical data were collected using a structured questionnaire and checklist, respectively. </span><span>Prothrombin time (PT) and activated partial thromboplastin time (APTT)</span><span> were analyzed by the HUMACLOT DUE PLUS<sup>®</sup> machine. Descriptive statistics were used to summarize the socio-demographic and clinical characteristics of study participants. Kruskal Wallis tests were used to compare the difference between parametric and non-parametric continuous variables, respectively. The area under the receiver operating characteristic curve (AUC) was used to evaluate the value of PT and APTT in the risk stratification and disease prognosis of COVID-19 patients. </span><span>Ordinal</span><span> logistic regression<span> was used to identify the factors associated with disease severity and prognosis</span>. </span><span>A P-value < 0.05 was defined as statistically significant for all results.</span></p> <p class="MsoNormal"><strong><span>Result</span></strong><span>:<strong> </strong></span><span>Baseline PT at a cut-off value <span class="red-underline">≥ </span>16.25 seconds differentiated severe COVID-19 patients from mild and moderate patients (AUC: 0.89, 95% CI: 0.83</span><span><span>–</span>0.95). PT also differentiated mild COVID-19 patients from moderate and severe patients at a cut-off value <span class="red-underline">≤ </span>15.35 seconds (AUC: 0.90, 95% CI: 0.84–0.96). Moreover, alcohol drinkers were 3.52 times more likely chance of having severe disease than non-drinkers (95% CI: 1.41–8.81). A one-year increment in age also increased the odds of disease severity by 6% (95% CI: 3</span><span><span>–</span>9%). An increment of </span><span>≥ 0.65 </span><span>seconds from the baseline<span> </span>PT predicted poor prognosis (AUC:</span><span> 0.93, 0.87–0.99)</span><span>. </span></p> <p class="MsoNormal"><strong><span>Conclusions and recommendations</span></strong><span>:</span><strong><span> </span></strong><span>Prolonged baseline PT was observed in severe COVID-19 patients. <span>Prolonged baseline PT was also predicted to worsen prognosis. An increase from the baseline PT was associated with worsen prognosis. Therefore, </span></span><span>PT can be used as a risk stratification and prognostic marker in COVID-19 patients.</span></p>
STRATIFICATION OF THE CLINICAL CONDITION OF ASTHMATIC PATIENTS AND THE IMPORTANCE OF APPROPRIATE MANAGEMENT
Open the record for dataset details and reuse information.
Geothermal heating affecting ocean stratification and circulation after the Last Glacial Maximum
<p>Data generated in this study is archived here.</p>
Effects of wind straining on estuarine stratification: A combined observational and modeling study
<p>Field data and model output</p>
Stellar models with calibrated convection and temperature stratification from 3D hydrodynamics simulations
<p>MESA T-tau data file associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.478.5650M/abstract">Stellar models with calibrated convection and temperature stratification from 3D hydrodynamics simulations</a></p>
All observational data for the study "Mixing, stratification and plankton under lake-ice: implications for summertime oxygen levels in the hypolimnion of a large lake"
<p>All field measurements of temperature, oxygen, conductivity, and velocity used in this study</p>
Data from: Immunohistochemical typing of adenocarcinomas of the pancreatobiliary system improves diagnosis and prognostic stratification
Background & Aims: Adenocarcinomas of the pancreatobiliary system are currently classified by their primary anatomical location. In particular, the pathological diagnosis of intrahepatic cholangiocarcinoma is still considered as a diagnosis of exclusion of metastatic adenocarcinoma. Periampullary cancers have been previously classified according to the histological type of differentiation (pancreatobiliary, intestinal), but overlapping morphological features hinder their differential diagnosis. We performed an integrative immunohistochemical analysis of pancreato-biliary tumors to improve their diagnosis and prediction of outcome. Methods: This was a retrospective observational cohort study on patients with adenocarcinoma of the pancreatobiliary system who underwent diagnostic core needle biopsy or surgical resection at a tertiary referral center. 409 tumor samples were analyzed with up to 27 conventional antibodies used in diagnostic pathology. Immunohistochemical scoring system was the percentage of stained tumor cells. Bioinformatic analysis, internal validation, and survival analysis were performed. Results: Hierarchical clustering and differential expression analysis identified three immunohistochemical tumor types (extrahepatic pancreatobiliary, intestinal, and intrahepatic cholangiocarcinoma) and the discriminant markers between them. Among patients who underwent surgical resection of their primary tumor with curative intent, the intestinal type showed an adjusted hazard ratio of 0.19 for overall survival (95% confidence interval 0.05–0.72; p value = 0.014) compared to the extrahepatic pancreatobiliary type. Conclusions: Integrative immunohistochemical classification of adenocarcinomas of the pancreatobiliary system results in a characteristic immunohistochemical profile for intrahepatic cholangiocarcinoma and intestinal type adenocarcinoma, which helps in distinguishing them from metastatic and pancreatobiliary type adenocarcinoma, respectively. A diagnostic immunohistochemical panel and additional extended panels of discriminant markers are proposed as guidance for their pathological diagnosis.
Data from: Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies
Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure. More generally, our results imply that typical constructions of polygenic scores are sensitive to population structure and that population-level differences should be interpreted with caution.
Data from: Lack of experience-based stratification in homing pigeon leadership hierarchies
In societies that make collective decisions through leadership, a fundamental question concerns the individual attributes that allow certain group members to assume leadership roles over others. Homing pigeons form transitive leadership hierarchies during flock flights, where flock members are ranked according to the average time differences with which they lead or follow others' movement. Here, we test systematically whether leadership ranks in navigational hierarchies are correlated with prior experience of a homing task. We constructed experimental flocks of pigeons with mixed navigational experience: half of the birds within each flock had been familiarized with a specific release site through multiple previous releases, while the other half had never been released from the same site. We measured the birds' hierarchical leadership ranks, then switched the same birds' roles at a second site to test whether the relative hierarchical positions of the birds in the two subsets would reverse in response to the reversal in levels of experience. We found that while across all releases the top hierarchical positions were occupied by experienced birds significantly more often than by inexperienced ones, the remaining experienced birds were not consistently clustered in the top half—in other words, the network did not become stratified. We discuss our results in light of the adaptive value of structuring leadership hierarchies according to 'merit' (here, navigational experience).
The added value of right ventricular function normalized for afterload to improve risk stratification of patients with pulmonary arterial hypertension
<p>Dataset of the paper</p>
Avascular Retina Area Modeling for Stratification Risk in Retinopathy of Prematurity
<p>Source data</p>
ScienceDex guides
Understand access before you commit
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.