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8 results for “imprecision”

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zenodo32/100

Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements (Replication Package)

<p>Replication package for Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements</p>

opencc-by-4.0Mar 2023View details →
zenodo32/100

Distribution. Central Highlands and E Madagascar (Andringitra National Park); also recorded from the vicinity of Antsirabe, Vinanitelo, and Ikongo in the E, but these localities are imprecise and therefore not mapped. in Tenrecidae

Distribution. Central Highlands and E Madagascar (Andringitra National Park); also recorded from the vicinity of Antsirabe, Vinanitelo, and Ikongo in the E, but these localities are imprecise and therefore not mapped.

opennotspecifiedJul 2018View details →
zenodo32/100

Artifact for "CTMCs with Imprecisely Timed Observations"

<p>This artifact contains an implementation of the approach from the paper&nbsp;<em>"CTMCs with Imprecisely Timed Observations" </em>presented at <em>TACAS 2024.</em><br>The implementation is written in Python and builds upon the probabilistic model checker <a href="https://www.stormchecker.org/">Storm</a>.<br>The artifact contains all benchmarks (CTMC models, properties, and evidences) used in the numerical experiments presented in Section 6 of the paper.<br>The artifact allows to reproduce all the results of the numerical experiments, in particular, Table 2 and Figure 6 (in the main paper) and Figure 8 (in the appendix).</p> <p>The artifact is licensed under GPL-3.0<br>Please see the <em>README</em> within the zip archive on how to obtain, build and run the artifact.</p> <p>&nbsp;</p> <p>Requirements:<br>No special requirements are needed, the artifact works without an internet connection.<br>Building the artifact requires 1-2 hours.<br>Running all experiments requires roughly 4 hours.</p>

opengpl-3.0-or-laterDec 2023View details →
zenodo28/100

Figure 2 from: Rome M, Coppens d'Eeckenbrugge G (2019) Imprecise descriptions of Passiflora riparia Martius ex Masters led to redundant descriptions as P. emiliae Sacco, P. crenata Feuillet & Cremers, P. pergrandis Holm-Nielsen & Lawesson and P. fernandezii Escobar. PhytoKeys 117: 1-27. https://doi.org/10.3897/phytokeys.117.30672

Figure 2 - Distribution of examined specimens of P.riparia (X), P.emiliae (red cross), P crenata (blue cross), P.fernandezii (green cross), P.pergrandis (purple cross), and the bioclimatic distribution model, highlighting climates that are marginal (grey), favorable (light yellow), very favorable (light orange) or excellent (bright orange). Black triangles represent distribution of examined specimens of P.ambigua.

opencc-by-4.0Feb 2019View details →
zenodo28/100

Figure 3 from: Rome M, Coppens d'Eeckenbrugge G (2019) Imprecise descriptions of Passiflora riparia Martius ex Masters led to redundant descriptions as P. emiliae Sacco, P. crenata Feuillet & Cremers, P. pergrandis Holm-Nielsen & Lawesson and P. fernandezii Escobar. PhytoKeys 117: 1-27. https://doi.org/10.3897/phytokeys.117.30672

Figure 3 - Representation of the climatic envelopes of P.riparia and its presumed synonyms in the principal plane of the PCA (same color code as for Figure 2). Passifloraambigua collections are represented by black triangles.

opencc-by-4.0Feb 2019View details →
zenodo28/100

Figure 1 from: Rome M, Coppens d'Eeckenbrugge G (2019) Imprecise descriptions of Passiflora riparia Martius ex Masters led to redundant descriptions as P. emiliae Sacco, P. crenata Feuillet & Cremers, P. pergrandis Holm-Nielsen & Lawesson and P. fernandezii Escobar. PhytoKeys 117: 1-27. https://doi.org/10.3897/phytokeys.117.30672

Figure 1 - Comparison between flowers of P.riparia and P.crenata.A–C flowers of P.riparia from Alta Floresta, Mato Grosso, Brazil (photo: Rich Hoyer) D flower of P.riparia from Marituba, Para, Brazil (photo: Luis Otavio Adão Teixeiro) E–H flowers of P.crenata from Cacao village, French Guiana. Flower size is indicated by 1 cm white bars.

opencc-by-4.0Feb 2019View details →
geo24/100

Imprecise DNMT1 activity coupled with neighbor-guided correction enables robust yet flexible epigenetic inheritance

GEO Series GSE116482. Mus musculus. 106 samples. Type: Methylation profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.

openGEO-OpenJul 2020View details →
zenodo20/100

Subspecies and Distribution. . t. theobaldi Dobson, 1872 - Tenasserim, Myanmar. . t. secatus Thomas, 1915 - Madhya Pradesh, India. Boundaries and complete distribution for subspecies are unknown, but T theobaldi is patchily distributed from C & SW India (Madhya Pradesh, Maharashtra, Karnataka, and Kerala), S China (Yunnan, imprecise locality and therefore not mapped), and SE Asia to Greater Sundas (Borneo, Java) and Sulawesi. Distribution is poorly known in India, and. theobaldi likely is more widespread than presently understood. It presumably will be found on other islands of the Indonesian Archipelago. in Emballonuridae

Subspecies and Distribution. . t. theobaldi Dobson, 1872 - Tenasserim, Myanmar. . t. secatus Thomas, 1915 - Madhya Pradesh, India. Boundaries and complete distribution for subspecies are unknown, but T theobaldi is patchily distributed from C &amp; SW India (Madhya Pradesh, Maharashtra, Karnataka, and Kerala), S China (Yunnan, imprecise locality and therefore not mapped), and SE Asia to Greater Sundas (Borneo, Java) and Sulawesi. Distribution is poorly known in India, and. theobaldi likely is more widespread than presently understood. It presumably will be found on other islands of the Indonesian Archipelago.

opennotspecifiedOct 2019View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record