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Record W2015932208 · doi:10.1088/2041-8205/739/2/l41

<i>M</i> -BAND IMAGING OF THE HR 8799 PLANETARY SYSTEM USING AN INNOVATIVE LOCI-BASED BACKGROUND SUBTRACTION TECHNIQUE

2011· article· en· W2015932208 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de MontréalHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPlanetPhotometry (optics)Background subtractionPlanetary systemTelescopeBrown dwarf

Abstract

fetched live from OpenAlex

Multi-wavelength observations/spectroscopy of exoplanetary atmospheres are the basis of the emerging exciting field of comparative exoplanetology. The HR 8799 planetary system is an ideal laboratory to study our current knowledge gap between massive field brown dwarfs and the cold 5 Gyr old solar system planets. The HR 8799 planets have so far been imaged at J - to L -band, with only upper limits available at M -band. We present here deep high-contrast Keck II adaptive optics M -band observations that show the imaging detection of three of the four currently known HR 8799 planets. Such detections were made possible due to the development of an innovative LOCI-based background subtraction scheme that is three times more efficient than a classical median background subtraction for Keck II AO data, representing a gain in telescope time of up to a factor of nine. These M -band detections extend the broadband photometric coverage out to ∼5 μm and provide access to the strong CO fundamental absorption band at 4.5 μm. The new M -band photometry shows that the HR 8799 planets are located near the L/T-type dwarf transition, similar to what was found by other studies. We also confirm that the best atmospheric fits are consistent with low surface gravity, dusty, and non-equilibrium CO/CH 4 chemistry models.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.226
Teacher spread0.202 · 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 designBench or experimental
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

Citations132
Published2011
Admission routes1
Has abstractyes

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