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Record W1992218070 · doi:10.1051/0004-6361/201015655

The first WASP public data release

2010· article· en· W1992218070 on OpenAlexfundno aff
O. W. Butters, R. G. West, D. R. Anderson, A. Collier Cameron, W. I. Clarkson, B. Enoch, C. A. Haswell, C. Hellier, K. Horne, Y. C. Joshi, S. R. Kane, Tim Lister, P. F. L. Maxted, N. Parley, D. Pollacco, B. Smalley, R. A. Street, Ian A. Todd, P. J. Wheatley, David M. Wilson

Bibliographic record

VenueAstronomy and Astrophysics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilQueen's UniversityQueen's University Belfast
KeywordsExoplanetLight curveSkyData setComputer sciencePlanetAstronomyThe InternetGeographyGeologyComputer graphics (images)Remote sensingPhysicsWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The WASP (wide angle search for planets) project is an exoplanet transit survey that has been automatically taking wide field images since 2004. Two instruments, one in La Palma and the other in South Africa, continually monitor the night sky, building up light curves of millions of unique objects. These light curves are used to search for the characteristics of exoplanetary transits. This first public data release (DR1) of the WASP archive makes available all the light curve data and images from 2004 up to 2008 in both the Northern and Southern hemispheres. A web interface () to the data allows easy access over the Internet. The data set contains 3 631 972 raw images and 17 970 937 light curves. In total the light curves have 119 930 299 362 data points available between them.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.997
Threshold uncertainty score0.615

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.015
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1840.257

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.211
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations369
Published2010
Admission routes1
Has abstractyes

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