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7 results for “Remote Viewing”

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zenodo40/100

Greg Kolodziejzyk's 13-year associative remote viewing experiment results

<p>The research that created this data is described in:</p> <ul> <li>Kolodziejzyk, G. (2012). Greg Kolodziejzyk's 13-year associative remote viewing experiment results.&nbsp;<em>The Journal of Parapsychology, 76</em>(2), 349.</li> </ul> <p>Five files are included:</p> <ul> <li>GregsARVdata2.txt - This is the raw data provided by Greg Kolodziejzyk</li> <li>Code book_0.txt - Code book (raw data)</li> <li>GregsARVdata2-dates-fixed.csv - Cleaned data (date formats standardised)</li> <li>Code book (cleaned data).pdf - Code book (cleaned data)</li> <li>Cleaning procedure_0.zip - Procedure for transforming from raw data to cleaned data.</li> </ul>

openodc-byMar 2017View details →
zenodo40/100

Greg Kolodziejzyk's 13-year associative remote viewing experiment results (session-level data)

<p>This dataset is a transformation of Greg Kolodziejzyk's remote viewing data (see Related datasets below). Greg used a "rapid-fire" technique whereby several short free-response remote viewing trials were completed in a single session. The trial-level data was transformed by Adrian Ryan into session-level Z-scores by exact binomial, in order that the data could be combined with those from other experiments, for the analyses reported here:</p> <ul> <li>Ryan, A., &amp; Spottiswoode, J. (2015). Variation of ESP by Season, Local Sidereal Time, and Geomagnetic Activity. Extrasensory Perception, 377-394.</li> </ul> <p>Three files are included:</p> <ul> <li>Data file</li> <li>Code book</li> <li>Transform Procedure: The R script used to transform the original trial-level data into session-level data.</li> </ul>

openodc-byApr 2017View details →
zenodo36/100

Transcontinental remote viewing

<p>The research that created this data is described in:</p> <ul> <li>Schlitz, M., &amp; Gruber, E. (1980). Transcontinental remote viewing.&nbsp;<em>The Journal of Parapsychology, 44</em>(4), 305.</li> </ul> <div>&nbsp;</div>

openodc-pddlApr 2017View details →
zenodo36/100

Remote viewing revisited: An intrasubject replication

<p>The research that created this data is described in:</p> <ul> <li>Schlitz, M. J., &amp; Haight, J. (1984). Remote viewing revisited: An intrasubject replication.&nbsp;<em>The Journal of Parapsychology, 48</em>(1), 39.</li> </ul>

openodc-pddlApr 2017View details →
ClinicalTrials.gov32/100

Operation of Brain Stimulation Equipment Under Remote Viewing Effectiveness Registry

ClinicalTrials.gov study NCT06512324. IPD Sharing: NO. Countries: 1. Publications: 5.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Service User and Staff Views on Digital Remote Monitoring for Psychosis

ClinicalTrials.gov study NCT05670197. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
nasa20/100

MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH

MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA* AND RANGA RAJU VATSAVAI* Abstract. Multispectral remote sensing images have been widely used for automated land use and land cover classification tasks. Often thematic classification is done using single date image, however in many instances a single date image is not informative enough to distinguish between different land cover types. In this paper we show how one can use multiple images, collected at different times of year (for example, during crop growing season), to learn a better classifier. We propose two approaches, an ensemble of classifiers approach and a co-training based approach, and show how both of these methods outperform a straightforward stacked vector approach often used in multi-temporal image classification. Additionally, the co-training based method addresses the challenge of limited labeled training data in supervised classification, as this classification scheme utilizes a large number of unlabeled samples (which comes for free) in conjunction with a small set of labeled training data.

restrictednotspecifiedApr 2025View 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