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Record W2764311032 · doi:10.3847/1538-3881/aacbcd

Time-resolved WISE/NEOWISE Coadds

2018· article· en· W2764311032 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsSkyProper motionPosition (finance)Span (engineering)Period (music)

Abstract

fetched live from OpenAlex

Abstract We have used the first ∼3 years of 3.4 μ m (W1) and 4.6 μ m (W2) observations from the WISE and NEOWISE missions to create a full-sky set of time-resolved coadds. As a result of the WISE survey strategy, a typical sky location is visited every six months and is observed during ≳12 exposures per visit, with these exposures spanning a ∼1 day time interval. We have stacked the exposures within such ∼1 day intervals to produce one coadd per band per visit—that is, one coadd every six months at a given position on the sky in each of W1 and W2. For most parts of the sky, we have generated six epochal coadds per band, with one visit during the fully cryogenic WISE mission, one visit during NEOWISE, and then, after a 33-month gap, four more visits during the NEOWISE-Reactivation mission phase. These coadds are suitable for studying long-timescale mid-infrared variability and measuring motions to ∼1.3 mag fainter than the single-exposure detection limit. In most sky regions, our coadds span a 5.5-year time period and therefore provide a >10× enhancement in time baseline relative to that available for the AllWISE catalog’s apparent motion measurements. As such, the signature application of these new coadds is expected to be motion-based identification of relatively faint brown dwarfs, especially those cold enough to remain undetected by Gaia .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations84
Published2018
Admission routes1
Has abstractyes

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