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.
697
datasets available to search
ShareScore release 0.9.0
Dataset results
697 results for “threshold”
Figure 2 in The study of fidelity measures in the context of using them as a threshold criterion in the allocation of diagnostic species
Figure 2. Representing distributions of some fidelity measures with different degree of asymmetry with kernel density estimates. From left to right: the case study of the test data set 1 and 2.
Fig. 1 in Threshold temperatures and thermal requirements of Psyllaphycus diaphorinae (Hymenoptera: Encyrtidae), a hyperparasitoid of Diaphorencyrtus aligarhensis (Hymenoptera: Encyrtidae) and Tamarixia radiata (Hymenoptera: Eulophidae)
Fig. 1. Predicted rate of total development as a function of temperature for Psyllaphycus diaphorinae (pooled males and females) at different constant and fluctuating temperatures using linear (a), Performance-2 (b), and Ratkowsky (c) models. In the linear and Perfomance-2 charts, the ordinate is the rate of development (1/D, per d), and the abscissa is temperature (°C). In the Ratkowsky chart (c) the ordinate is the square root of development rate (, per d), and the abscissa is temperature (°C). Symbols represent mean observed data. Solid lines represent model predictions for fluctuating temperatures and dashed lines for constant temperatures. For linear regression (a), data values for 32 °C were omitted because of significant deviation from rectilinearity.
Main output data used in "Exploring the Greenland Ice Sheet's response to future atmospheric warming-threshold scenarios over 200 years" (Delhasse et al., 2025)
<p>Outputs used in:</p> <p>Delhasse, A., Kittel, C. and Beckmann, J.: Exploring the Greenland Ice Sheet's response to future atmospheric warming-threshold scenarios over 200 years, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-709, 2025.</p> <p>Each MAR-PISM coupling experiment (1991-2200) is related to the Greenland warming over a 10-year period compared to our reference period (1961-1990) at which climate is stabilized until 2200. The last experiment is the Reverse one, where the climate is year by year reversed after 2100 to go back to 2000-climate as forcing in 2200, the last year of the simulation. Please refer to Delhasse et al. (2024) for the coupling description.</p> <div> <table> <tbody> <tr> <th> <p>Experiment </p> </th> <th> <p>Exact Greenland warming at 600hPa (°C)</p> </th> <th> <p>10-years period</p> </th> </tr> </tbody> <tbody> <tr> <td> <p>CTRL</p> </td> <td> <p>+0.00</p> </td> <td> <p>1961-1990</p> </td> </tr> <tr> <td> <p>+1</p> </td> <td> <p>+1.04</p> </td> <td> <p>1995-2004</p> </td> </tr> <tr> <td> <p>+1.5</p> </td> <td> <p>+1.51</p> </td> <td> <p>2010-2019</p> </td> </tr> <tr> <td> <p>+2</p> </td> <td> <p>+2.04</p> </td> <td> <p>2021-2030</p> </td> </tr> <tr> <td> <p>+3</p> </td> <td> <p>+2.98</p> </td> <td> <p>2040-2049</p> </td> </tr> <tr> <td> <p>+4</p> </td> <td> <p>+4.04</p> </td> <td> <p>2058-2067</p> </td> </tr> <tr> <td> <p>+5</p> </td> <td> <p>+5.00</p> </td> <td> <p>2074-2083</p> </td> </tr> <tr> <td> <p>+6</p> </td> <td> <p>+5.96</p> </td> <td> <p>2083-2092</p> </td> </tr> <tr> <td> <p>+7</p> </td> <td> <p>+6.85</p> </td> <td> <p>2091-2100</p> </td> </tr> </tbody> </table> </div> <p><strong>Table 1. Greenland warmings at 600hPa since 1961-1990 used to define our experiments and the corresponding 10-years periods over which warmings are determined. </strong></p> <p>For each experiment, 3 types of output are available (where <em>EXP</em> corresponds to the name of the experiment as referenced in Table 1) : </p> <ul> <li> <p>EXP-PISM-thk-msk-1991-2200.nc: contain yearly ice thickness (THK) and ice mask (MASK) as simulated by PISM (PISM grid, 4.5 km);</p> </li> <li> <p>EXP-SMB-ME-RU-MAPI-CESM2-1991-2200.nc: contain yearly SMB (surface mass balance), ME (melt), and RU (runoff) on the MAR grid (25 km);</p> </li> <li> <p>EXP-ts-MB-D-SMB-1991-2200.nc: contain time series of the total MB (mass balance), D (discharge), and SMB (surface mass balance) integrated over the all ice sheet mask from PISM.</p> </li> </ul> <p>The MAR code used in this dataset is tagged as v3.11.3 on https://gitlab.com/Mar-Group/MARv3/-/tree/v3.11.3 (last access: 24 October 2024) (MARTeam, 2024). The PISM code used is tagged as PISMv1.2.2 on <a href="https://github.com/pism/pism/releases/tag/v1.2.2">https://github.com/pism/pism/releases/tag/v1.2.2</a> (last access: 24 October 2024).</p> <p>If you need other variables from MAR or PISM, send us an email (alison.delhasse@uliege.be) and we will be glad to help you. We will also be happy to share the scripts we have developed to analyze the outputs and make the figures in this paper if needed. Please cite the paper if you use these MAR-PISM outputs.<br><br><strong><em>Data usage notice:</em></strong></p> <p>If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgments should be similar to the one below that contains information related to MAR and PISM. To document MAR scientific impact and enable ongoing support of the model, users are likely encouraged to contact me to add their works to the list of MAR-related publications. </p> <p>"We thank A. Delhasse, C. Kittel, and J. Beckmann, as well as the MAR and PISM teams which make available the model outputs. We also thank agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR-PISM simulations. "</p> <p>You should also refer to and cite the following paper in its latest version:</p> <p>Delhasse, A., Kittel, C. and Beckmann, J.: Exploring the Greenland Ice Sheet’s response to future warming-threshold scenarios over 200 years, [JOURNAL UNDER REVIEW], 2024.</p> <p><strong><em>References</em></strong></p> <p>Delhasse, A., Beckmann, J., Kittel, C., and Fettweis, X.: Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback, The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, 2024.</p> <p>MARTeam: MARv3.11, GitLab [data set], <a href="https://gitlab.com/Mar-Group/MARv3">https://gitlab.com/Mar-Group/MARv3#</a> (last access: 24 October 2024), 2024.</p> <p> </p>
Tracking cell migration with the TrackMate threshold detector
<p>Migrating cells tracked with TrackMate, using the threshold detector.</p> <p>For more information see https://imagej.net/plugins/trackmate/trackmate-thresholding-detector</p> <p> </p>
Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies
<p><span>Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding datasets, therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences in Molecular Operational Taxonomic Units (MOTUs), each of which ideally representing a homogeneous taxonomic entity, e.g. a species or a genus. However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g. Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate a careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.</span></p>
Data for the paper "Optimizing Duplicate Size Thresholds in IDEs"
<p>Here you can find data for the paper "Optimizing Duplicate Size Thresholds in IDEs". </p> <p> </p> <ul> <li>In Archive_in.zip, one can find raw files that were used in the analysis. The archive is already structured to be used in the Lupa pipeline. For further instructions for replication, refer to <a href="https://github.com/nbirillo/clone-detector/tree/python-clone-analysis">our realisation of algorithm </a>and <a href="https://github.com/nbirillo/Lupa">Lupa</a> GitHub pages. </li> <li>In Archive_out.zip, one can find results of deduplication algorithm, which are used in the analysis. For each processed file there is a corresponding JSON, which contains meta-information about the file and a list of group of clones. </li> </ul> <p>Code and results can be find <a href="https://github.com/JetBrains-Research/jupyter-python-clones">here</a>.</p>
Interaural Time Difference discrimination threshold determined through three alternative 2I-2AFC procedures
<p>The present dataset has been collected through an experiment on fast ITD discrimination thresholds determination. Each participant was sitting in front of the laptop computer running the GUI during the test. At each trial, the task consisted of listening to two subsequent and randomly balanced stimuli, and then choosing which sound was the rightmost, by selecting it with the mouse on the computer screen. At the beginning of each session, five pilot trials were presented having ITD levels equal to 240, 200, 160, 120, and 80 μs. Correct guesses in all such trials were necessary for the measurements to start in correspondence with the sixth trial. The session lasted approximately 10 minutes. The protocol was designed for determining the PF 79.4% threshold, describing the subjective lateralization performance as a function of T defined as half of the actual ITD to be discriminated. The target (i.e., rightmost) stimulus was lateralized twice as much as a nominal ITD, and the reference source (i.e., leftmost) stimulus was instead lateralized with an opposite ITD. Hence, an ITD threshold equal to 2T means that a participant discriminated the target ITD by T μs from the reference ITD of −T μs. The protocol implemented three different procedures:<br> • adaptive 'three down, one up' two-interval 2AFC (2I-2AFC hereafter),<br> • Gaussian Process Classification (GPC) with Bayesian Active learning by disagreement (BALD) (BALD hereafter),<br> • GPC with random acquisition function (RANDOM hereafter).<br> Accordingly, every session included three series of trials respectively implementing such procedures in a randomly balanced order. When GPC was used, thus enabling active learning and random selection of ITDs, the number of trials was empirically set to 15.</p> <p>In the dataset you will find:</p> <p>- Participant: IDs of the participant<br> - Age: age of the participant<br> - Gender: gender of the participant<br> - ITD_2AFC: T values presented in the 2I-2AFC procedure<br> -LABEL_2AFC: binary labels for the right (1) or wrong (0) answers in the 2I-2AFC procedure<br> - PRED_2AFC: Weibull fitting predictions on 1-100 microseconds<br> - ITD_BALD: T values presented in the BALD procedure<br> - LABEL_BALD: binary labels for the right (1) or wrong (0) answers in the BALD procedure<br> - MEANS_BALD: means of the GPC Bernoulli likelihood computed on 1-100 microseconds at each iteration step in the BALD procedure<br> - VARS_BALD: variances of the GPC Bernoulli likelihood computed on 1-100 microseconds at each iteration step in the BALD procedure<br> - MEANS_LATENT_BALD: means of the latent GPC prior computed on 1-100 microseconds at each iteration step in the BALD procedure<br> - VARS_LATENT_BALD: variances of the latent GPC prior computed on 1-100 microseconds at each iteration step in the BALD procedure<br> - ITD_RAND: T values presented in the RANDOM procedure<br> - LABEL_RAND: binary labels for the right (1) or wrong (0) answers in the RANDOM procedure<br> - MEANS_RAND: means of the GPC Bernoulli likelihood computed on 1-100 microseconds at each iteration step in the RANDOM procedure<br> - VARS_RAND: variances of the GPC Bernoulli likelihood computed on 1-100 microseconds at each iteration step in the RANDOM procedure<br> - MEANS_LATENT_RAND: means of the latent GPC prior computed on 1-100 microseconds at each iteration step in the RANDOM procedure<br> - VARS_LATENT_RAND: variances of the latent GPC prior computed on 1-100 microseconds at each iteration step in the RANDOM procedure</p>
Data, Scripts underlying the publication: Identifying the critical turbidity threshold to maintain estuarine tidal flats worldwide
<p>Data & Scripts featured in the currently unpublished manuscript (as of 21-07-2023) Grandjean et al.: 'Identifying the critical turbidity threshold to maintain estuarine tidal flats worldwide'. This study explores the relationship between tidal range and turbidity concentrations on the morphological trajectory of unvegetated tidal flats at a global scale. These files include the scripts used to produce digital elevation models per estuary.</p> <p> </p>
Data from: Estimating a physiologically-based threshold to oxygen and temperature from marine monitoring data reveals challenges and opportunities for forecasting distribution shifts
Open the record for dataset details and reuse information.
Data for: Plant thresholds and community composition of coastal marsh-forest ecotones in the US Northeast
Open the record for dataset details and reuse information.
Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies
Open the record for dataset details and reuse information.
Reference genome choice and filtering thresholds jointly influence phylogenomic analyses
Open the record for dataset details and reuse information.
Data from: Defining the pyro-thermal niche: do seed traits, ecosystem type and phylogeny influence thermal thresholds in seeds with physical dormancy
Open the record for dataset details and reuse information.
Wildfires and climate change push low-elevation forests across a critical climate threshold for tree regeneration
Open the record for dataset details and reuse information.
Data from: Soil moisture threshold of methane uptake in alpine ecosystems
Open the record for dataset details and reuse information.
Thresholds and alternative states in neotropical dry forest in response to fire severity, 2005-2018
Neotropical xerophytic forest ecosystems evolved with fires that shaped their resilience to disturbance events. We asked if there is evidence for a fire severity threshold causing an abrupt transition from a forest to an alternative shrub thicket state in the presence of typical post-fire management. We studied a heterogeneous wildfire event to assess medium-term effects (11 years) of varying fire severity in a xerophytic Caldén forest (Prosopis caldenia) in La Pampa province, central Argentina. We conducted field vegetation surveys in patches that were exposed to low (LFS), medium (MFS), and high (HFS) fire severities, but had similar pre-fire woody canopy cover. Satellite images were used to quantify fire severity using a delta Normalized Burning Ratio (dNBR) and to map pre-fire canopy cover. The structure and composition of woody and herbaceous vegetation was measured during the 2017-18 growing season (September to March) in areas affected by different severities of the 2006 wildfire.
Data for: Thresholds of freshwater biodiversity in response to riparian vegetation loss in the Neotropical region
<p>These files contain all the data and R scripts used for analyses of the manuscript "Thresholds of freshwater biodiversity in response to riparian vegetation loss in the Neotropical region", published in Journal of Applied Ecology.</p> <p>See Metadata (README).xls file for a detailed description of these files.</p> <p>Dala-Corte RB, Melo AS, Siqueira T, et al. Thresholds of freshwater biodiversity in response to<br> riparian vegetation loss in the Neotropical region. J Appl Ecol. 2020;00:1–12. https://doi.org/10.1111/1365-2664.13657</p>
Potential for powered flight neared by most close avialan relatives but few crossed its thresholds
<p>This dataset is the Supplementary Materials of the Pei, Pittman <em>et al</em>. (2020) study 'Potential for powered flight neared by most close avialan relatives but few crossed its thresholds' in Current Biology (<a href="https://doi.org/10.1016/j.cub.2020.06.105" rel="noreferrer noopener" title="Persistent link using digital object identifier">https://doi.org/10.1016/j.cub.2020.06.105</a>). In this study, a revised phylogeny of coelurosaurian theropod dinosaurs was used to reconstruct their potential for powered flight. It found that powered flight potential evolved at least three times (once in birds and twice in dromaeosaurids) and that many ancestors of close bird relatives neared thresholds of powered flight potential. The latter suggests that there was broad experimentation with wing-assisted locomotion before theropod flight evolved. This dataset contains an expanded version of the Theropod Working Group (TWiG) coelurosaurian theropod phylogenetic data matrix (revised after Brusatte <em>et al</em>. 2014). It also contains the script and results associated with an automated parsimony-based phylogenetic analysis of the data matrix. This dataset includes the wing loading and specific lift proxy data used to reconstruct flight potential in the pennaceous feathered pennaraptoran theropods listed in the taxon list as well as the results of the parsimony- and maximum-likelihood based mapping of these proxies over the reconstructed tree topology. Forelimb length [(humerus length + ulna length)/femoral length] and body size data are also included as well as the results of the parsimony- and maximum-likelihood based mapping of these parameters over the same tree topology. Please read the following files before navigating the dataset: README.pdf and Instructions for zip file use - please read this first.pdf</p>
Raw data: Effect of the Relative Timing between Same-Polarity Pulses on Thresholds and Loudness in Cochlear Implant Users
<p>Raw values in dB re. 1 µV of the thresholds and loudness-balanced levels at MCL from:</p> <p>Guérit, F., Marozeau, J., Epp, B., & Carlyon, R. P. (2020). Effect of the Relative Timing between Same-Polarity Pulses on Thresholds and Loudness in Cochlear Implant Users. <em>Journal of the Association for Research in Otolaryngology</em>, 1–14. doi:10.1007/s10162-020-00767-y</p>
Accelerated landings in stingless bees are triggered by visual threshold cues
<p>Most flying animals rely primarily on visual cues to coordinate and control their trajectory when landing. Studies of visually-guided landing typically involve animals that decrease their speed before touchdown. Here, we investigate the control strategy of the stingless bee <i>Scaptotrigona depilis</i>, which instead accelerates when landing on its narrow hive entrance. By presenting artificial targets that resemble the entrance at different locations on the hive, we show that these accelerated landings are triggered by visual cues. We also found that <i>S. depilis</i> initiated landing and extended their legs when the angular size of the target reached a given threshold. Regardless of target size, the magnitude of acceleration was the same and the bees aimed for the same relative position on the target suggesting that <i>S. depilis</i> use a computationally simple but elegant 'stereotyped' landing strategy that requires few visual cues.</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.