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Target selection for the SUNS and DEBRIS surveys for debris discs in the solar neighbourhood

2010· article· en· W2169189696 on OpenAlexaff
N. Phillips, J. S. Greaves, W. R. F. Dent, Brenda C. Matthews, W. S. Holland, M. C. Wyatt, B. Sibthorpe

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of Astrophysics
FundersScience and Technology Facilities Council
KeywordsSuns in alchemyPhysicsJames Clerk Maxwell TelescopeBolometerPhotometry (optics)AstronomyAstrophysicsObservatorySolar SystemDebrisStarsRemote sensingStar formationOpticsMeteorologyDetector

Abstract

fetched live from OpenAlex

Debris discs - analogous to the Asteroid and Kuiper-Edgeworth belts in the Solar system - have so far mostly been identified and studied in thermal emission shortward of 100 um. The Herschel space observatory and the SCUBA-2 camera on the James Clerk Maxwell Telescope will allow efficient photometric surveying at 70 to 850 um, which allow for the detection of cooler discs not yet discovered, and the measurement of disc masses and temperatures when combined with shorter wavelength photometry. The SCUBA-2 Unbiased Nearby Stars (SUNS) survey and the DEBRIS Herschel Open Time Key Project are complimentary legacy surveys observing samples of ~500 nearby stellar systems. To maximise the legacy value of these surveys, great care has gone into the target selection process. This paper describes the target selection process and presents the target lists of these two surveys.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.005

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations55
Published2010
Admission routes1
Has abstractyes

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