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.
4,245
datasets available to search
ShareScore release 0.9.0
Dataset results
4,245 results for “Diagnostic”
FIG. 8 in New diagnostic microcharacters of the cephalothoracic appendages in Cyclops O. F. Müller, 1776 (Crustacea, Copepoda, Cyclopoida)
FIG. 8. — Ornamentation of the maxillular palp, and setulation of the palp setae, female; A, B, Cyclops heberti Einsle, 1996; A, Germany, paratype; B, Poland, Wigry (Cyclops strenuus strenuus Fischer, 1851 sensu Koźmiński, 1933); C, C. scutifer Sars, 1863 (Norway, Maridalsvann); D, C. columbianus Lindberg, 1956 (Alaska, Karluk lake[?]); E, C. kolensis Lilljeborg, 1901 (Poland, L. Wigry); F, C. alaskaensis Lindberg, 1956 (Alaska); G, C. insignis Claus, 1857 (Norway, Frognertjern). Scale bar: 50 µm.
FIG. 11 in New diagnostic microcharacters of the cephalothoracic appendages in Cyclops O. F. Müller, 1776 (Crustacea, Copepoda, Cyclopoida)
FIG. 11. — Setulation of the medial spine and ornamentation of the frontal surface of P1 basipodite, female; A, Cyclops strenuus Fischer, 1851 (Russia, Peterhof); B, C. insignis Claus, 1857 (Norway, Frognertjern); C, C. singularis Einsle, 1996 (Germany, paratype); D, C. canadensis Einsle, 1988 (Alaska, Point Barrow). Scale bars: 50 µm.
FIG. 12 in New diagnostic microcharacters of the cephalothoracic appendages in Cyclops O. F. Müller, 1776 (Crustacea, Copepoda, Cyclopoida)
FIG. 12. — Setulation of the medial spine and ornamentation of the frontal surface of P1 basipodite, female; A, Cyclops abyssorum Sars, 1863 (Norway, Lønavatn); B, C. kolensis Lilljeborg, 1901 (Poland, L. Wigry); C, C. furcifer Claus, 1857 (Germany, Baden); D, C. alaskaensis Lindberg, 1956 (Alaska). Scale bar: 50 µm.
FIG. 5 in New diagnostic microcharacters of the cephalothoracic appendages in Cyclops O. F. Müller, 1776 (Crustacea, Copepoda, Cyclopoida)
FIG. 5. — Spinule ornamentation on the caudal surface of the antennal coxobasis, female; A, B, Cyclops heberti Einsle, 1996; A, Germany, Oldenburg; B, Germany (paratype); C, D, C. scutifer Sars, 1863; C, Norway, Maridalsvann; D, Norway, Lønavatn; E, F, C. insignis Claus, 1857 (Norway, Frognertjern); G, C. columbianus Lindberg, 1956 (Alaska, Karluk lake[?]). Scale bar: 50 µm.
Reproduction package for the paper "Host Galaxy Line Diagnostics for the Candidate Tidal Disruption EventsXMMSL1 J111527.3+180638 and PTF09axc"
<p>This is a reproduction package for the paper "Host Galaxy Line Diagnostics for the Candidate Tidal Disruption EventsXMMSL1 J111527.3+180638 and PTF09axc" containing the final data products as well as all scripts for data analysis and creating the figures present in the paper. </p>
Exploring the Diagnostic Markers of Essential Tremor: A study based on Machine Learning Algorithms
<p>supplementary information files for the manuscript Exploring the Diagnostic Markers of Essential Tremor: A study based on Machine Learning Algorithms</p>
CausalOrca: An ORCA-based Diagnostic Dataset for Causally-aware Multi-agent Trajectory Prediction
<p>CausalOrca is a synthetic diagnostic dataset created through controlled simulations. It is designed to provide annotations of ground-truth causal effects and fine-grained agent categories for social interactions in multi-agent scenarios. The dataset is constructed using a modified RVO2 simulator and incorporates the ORCA optimization-based collision avoidance algorithm known for crowd simulation. With full control over scene configurations, the dataset enables the collection of motion behaviors in paired scenes before and after agent removal, generating a large set of counterfactual pairs with annotations of ground-truth causal effects. CausalOrca can serve as a valuable resource for studying and developing causally-aware neural representations of social interactions and trajectory prediction models. Please see the <a href="https://github.com/rebuttal-anonymous/causalorca">GitHub repository</a> for a more detailed description of the dataset, including dataset statistics and documentation on how to use, visualize, and generate the data.</p>
[Dataset] Pattern and repeatability of ascarid-specific antigen excretion through chicken faeces, and the diagnostic accuracy of copro-antigen measurements as compared with McMaster egg counts and plasma and egg yolk antibody measurements in laying hens
<p>Comprehensive data examining the pattern and repeatability of ascarid-specific antigen excretion in chicken faeces and the diagnostic accuracy of copro-antigen measurements compared to McMaster egg counts and antibody measurements in laying hens.</p> <p>The dataset consists of observations and measurements obtained from a controlled study involving laying hens infected with mixed <em>Ascaridia galli</em> and<em> Heterakis gallinarum</em>. A total of 179 individual hens were monitored between wpi 2 and 18 and their fecal samples/blood samples were collected at specific time points. Faecel samples were repeatedly collected four(4) consecutive times in one wpi.Hence antigen measurements is 4 X 179 = 716 measurements</p>
Fig 1 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig 1. Selected frogs in the Litoria graminea (A–B) and Litoria infrafrenata (C–F) groups that occur in the western (Indonesian) half of New Guinea. A, Litoria huntorum from the foothills of the Foja Mountains, B, L. pallidofemora from Batanta Island, C, Litoria infrafrenata from Batanta Island, D, Litoria lubisi from Timika region, E, Litoria multicolor from the Wondowoi Mountains, and F, Litoria purpureolata from Biak Island. Note the typically less extensive webbing on the fingers and toes of species in the Litoria infrafrenata group. Photographs: A–D, Stephen Richards, E–F, Rainer Günther.
Fig. 4 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig. 4. Details of Litoria azuroscelis, new species, holotype MZB Amph. 32893 in preservative. A, Details of eye showing largely unpigmented nictitating membranes, B, dorsal view of head, C, details of hand show moderately extensive webbing, and D, whole animal showing colouration in preservative.
Fig. 2 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig. 2. Details of nuptial excrescences in frogs from the Litoria infrafrenata (A–B) and Litoria graminea groups (C–F). A, Litoria purpureolata, B, Litoria lubisi, C, L. pallidofemora, D, L. pterodactyla, E, L. huntorum, and F, L. azuroscelis, new species. Note very fine excrescences in the two species from the Litoria infrafrenata group (A and B).
Fig 3 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig 3. Litoria azuroscelis, new species, holotype MZB Amph. 32893 in life. A, lateral view, B, more dorsal view highlighting blue wash on groin and hidden surfaces of hindlimbs. Photographs: Rainer Günther.
Fig. 7 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig. 7. Forest interior at Maja Waterfall, Papua Barat Province, Indonesia, the type locality of Litoria azuroscelis, new species. Photograph: Rainer Günther.
Fig. 5. A in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig. 5. A, Spectrogram of male Litoria azuroscelis, new species, and B, amplitude spectrum for calls in 5A. Calls recorded at 25°C.
Fig. 6 in A new large green treefrog (Litoria: Pelodryadidae) from western New Guinea, with the description of a new diagnostic character for the Litoria graminea group
Fig. 6. Map of New Guinea with the type locality of Litoria azuroscelis, new species, at the base of the Wandammen Peninsula indicated by a red star.
Scripts and datas for "Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance"
<p>Input and output datasets used for a global reconstruction of the eddy kinetic energy (EKE) dissipation rate in relation to a submitted work :</p> <p><strong>R. Torres, R. Waldman, J. Mak and R. Séférian </strong>: <em>Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance</em>.</p> <p>Inputs datas include a merge of 2 datasets from the World Ocean Atlas 2018 (WOA18, Garcia et al., 2019) and cover the 1995-2017 (95B7) period. Folder structure for the surface altimetry L4 datasets from the EU-Copernicus Marine Services (2021) is kept empty in order to limit the archive size. Datas can be download <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047/services">here</a>.</p> <p>Optional datasets include CMEMS MDT product (<em>CMEMS/SEALEVEL_GLO_PHY_MDT_008_063/P20Y</em>) downloaded <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_MDT_008_063/">here</a> and ocean masks (<em>misc/basins/doi_10.5281</em>) from Martinez-Moreno et al. (2021).</p> <p>In addition, simulation outputs from the NEMO-OMIP2 model runned with the GEOMETRIC parameterization are processed (mainly time-averaged) and stored in <em>CNRM/runs/omip2_LR.Geom_Emin0-alpha01_1cyc-trd/post</em>. These files are used in the uncertainties and errors quantification.</p> <p>Outputs and published results are stored in each individual product post-processing folder while final EKE dissipation computation are located in the <em>EKE_dissipation_rate</em> folder since it results from a combination of multiple products.</p> <p>IPython notebooks for computing and plotting global maps are also provided :</p> <ul> <li><em>1-post_process_climato.ipynb</em> : compute from the climatology (e.g. WOA18 datas) the EKE dissipation timescales (units in days) and the surface modes with rough topography (LaCasce and Groeskamp, 2020).</li> <li><em>2-post_process_altimetry.ipynb</em> : compute from altimetry (CMEMS) datasets the EKE at surface and eventually coarsen the grid from 0.25 to 1 degree in order to match the climatology grid.</li> <li><em>3-compute_global_eke_dissipation.ipynb</em> : combine both outputs from the two above scripts to compute the global EKE dissipation. The script also plots new maps.</li> <li><em>0-plot_global_maps.ipynb</em> : plot the global maps for climatology and altimetry products.</li> <li><em>0-plot_lbekedis_ogcm.ipynb</em> : plot and analyse EKE timescale errors from the NEMO-OMIP2 simulation outputs.</li> </ul> <p>Note however that these scripts use the author python library XOCE availbale on GitHub: https://github.com/torresr-cnrm/xoce. All the scripts have been runned using the version 0.2 of XOCE. Feel free to contact (romain.torres@meteo.fr) for any help in installing and using this library.</p>
A Single Dose Pharmaco-Diagnostic for Peripheral Nerve Continuity After Trauma
ClinicalTrials.gov study NCT04026568. IPD Sharing: NO. Countries: 1. Publications: 28.
Study of Diagnostic Performance of [18F]CTT1057 in BCR
ClinicalTrials.gov study NCT04838613. IPD Sharing: YES. Countries: 4. Publications: 0.
Study of Diagnostic Performance of [18F]CTT1057 for PSMA-positive Tumors Detection
ClinicalTrials.gov study NCT04838626. IPD Sharing: YES. Countries: 5. Publications: 0.
Panitumumab and RAS, Diagnostically-useful Gene Mutation for mCRC
ClinicalTrials.gov study NCT02394795. IPD Sharing: YES. Countries: 1. Publications: 3.
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.