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56 results for “False positives”

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zenodo28/100

Notebook & Data for "False positives are common in single-station template matching"

<p>Computational notebook &amp; associated data files used for the paper &quot;False positives are common in single-station template matching&quot; in Seismica by J.B. Muir et al.&nbsp;</p>

opencc-by-4.0Jul 2023View details →
ClinicalTrials.gov28/100

Safety, False-Positive Reactions and Sensitizing Properties of Leishmania Tropica Skin Test Antigen

ClinicalTrials.gov study NCT00633009. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

The Incidence and Incubation Period of False Positive Cultures in Shoulder Surgery

ClinicalTrials.gov study NCT02602548. IPD Sharing: YES. Countries: 0. Publications: 2.

controlledIPD-YESFeb 2026View details →
dryad28/100

Data from: Recognizing false positives: synthetic oligonucleotide controls for environmental DNA surveillance

Open the record for dataset details and reuse information.

publicSep 2015View details →
dryad28/100

Data from: On the occurrence of false positives in tests of migration under an isolation with migration model

Open the record for dataset details and reuse information.

publicJul 2015View details →
geo24/100

Active Promoters give rise to false positive 'Phantom Peaks' in ChIP-Seq experiments

GEO Series GSE67323. Drosophila melanogaster. 26 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenJul 2015View details →
zenodo24/100

Face detection ensemble with methods using depth information to filter false positives

<p>%files (File.rar):<br> %ColorImageX.jpg is the color image<br> %SegImageX.jpg is the segmentation map&nbsp;<br> %SegImage2_X.jpg is the segmentation map obtained considering only Depth<br> %map</p> <p>%the .mat file<br> %DatasetFaceD{x}{1} depth map<br> %DatasetFaceD{x}{2} eyes coordinates<br> %DatasetFaceD{x}{3} calibration matrix, e.g used in face_dimension.m</p> <p>&nbsp;</p> <p>PS few images (7) used in the paper are no more available</p> <p>&nbsp;</p>

opencc-by-4.0Jun 2020View details →
dryad24/100

Data from: Measurement artefacts lead to false positives in the study of birdsong in noise

1: Numerous studies over the past decade have reported correlations between elevated levels of anthropogenic noise and a rise in the minimum frequency of acoustic signals of animals living in noisy habitats. This pattern appears to be occurring globally, and higher pitched signals have been hypothesized to be adaptive changes that reduce masking by low-frequency traffic noise. However, the sound analysis methods most often used in these studies are prone to measurement errors that can result in false positives. In addition, the commonly used method of measuring frequencies visually from spectrograms might also lead to observer-expectancy biases that could exacerbate measurement errors. 2: We conducted an experiment to (a) quantify the size and type of errors that result from "eye-balling" frequency measurements with cursors placed manually on spectrograms of signals recorded in noise and no-noise conditions, and (b) to test whether observer expectations lead to significant errors in frequency measurements. We asked 54 volunteers, blind to the true intention of our study, to visually measure the minimum frequency of a variety of natural and synthesized bird sounds, recorded either in noise, or no-noise conditions. Test subjects were either informed or uninformed about the hypothesized results of the measurements. 3: Our results demonstrate that inappropriate methodology in acoustic analysis can yield false positives with effect sizes as large, or even larger, than those reported in published studies. In addition to these measurement artefacts, psychological observer biases also led to false positives – when observers expected signals to have higher minimum frequencies in noise, they measured significantly higher minimum frequencies than uninformed observers, who had not been primed with any expectation. 4: The use of improper analysis methods in bioacoustics can lead to the publication of spurious results. We discuss alternative methods that yield unbiased frequency measures and we caution that it is imperative for researchers to familiarize themselves both with the functions and limitations of their sound analysis programs.. In addition, observer expectancy biases are a potential source of error not only in the field of bioacoustics, but in any situation where measurements can be influenced by human subjectivity.

opencc-zeroDec 2016View details →
ClinicalTrials.gov24/100

Characteristics of Mediastinal Lymph Node With False Positive FDG PET/CT Results in Lung Cancer Staging : Relation With TB and Latent TB Infection

ClinicalTrials.gov study NCT01376856. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

FALSE POSITIVE FINDINGS IN BREAST CANCER TOMOSYNTHESIS

ClinicalTrials.gov study NCT04259866. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Reducing False Positives in Prenatal Screening

ClinicalTrials.gov study NCT03375359. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

False Positive Peripheral Blood Culture in Children With Leukaemia: A Prevalence Study

ClinicalTrials.gov study NCT06336837. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad24/100

Data from: Measurement artefacts lead to false positives in the study of birdsong in noise

Open the record for dataset details and reuse information.

publicMar 2018View details →
ClinicalTrials.gov20/100

Anti-HIV False Positivity Rate in Pregnant Women; and Investigating the Factors Affecting This Situation

ClinicalTrials.gov study NCT03777371. IPD Sharing: YES. Countries: 0. Publications: 0.

controlledIPD-YESFeb 2026View details →
zenodo12/100

Integrated N-mixture models generally perform well against other models for false positive prone data in ecological applications

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restrictedcc-by-4.0Jun 2024View details →
zenodo12/100

The false positive problem: An assessment of integrated abundance and occupancy models where false positives are present in ecological data.

Open the record for dataset details and reuse information.

restrictedcc-by-4.0Oct 2024View 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