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Record W4405821804 · doi:10.3847/1538-4365/ad90a4

Reduction and Archiving of Multiwavelength, Polarized-intensity Debris-disk Observations with the Gemini Planet Imager

2024· article· en· W4405821804 on OpenAlexfundno aff
Katie A. Crotts, Thomas M. Esposito, Brenda C. Matthews, Gaspard Duchêne, Christine Chen, Justin Hom, Paul Kalas, B. Lewis, Stanimir Metchev, Maxwell A. Millar‐Blanchaer, Deborah Padgett, Marshall D. Perrin, Bin Ren

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryComisión Nacional de Investigación Científica y TecnológicaNatural Sciences and Engineering Research Council of CanadaMinistério da Ciência, Tecnologia e InovaçãoEuropean Space AgencyNational Aeronautics and Space AdministrationU.S. Department of EnergyMinisterio de Ciencia, Tecnología e Innovación ProductivaNational Science Foundation
KeywordsPlanetDebris diskDebrisReduction (mathematics)AstrobiologyRemote sensingIntensity (physics)AstronomyGeologyPhysicsEnvironmental scienceOpticsPlanetary systemMeteorologyMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract The Gemini Planet Imager (GPI), an extreme adaptive optics instrument on Gemini South, has been pivotal in the advancement of the debris-disk field. Over the past decade, GPI has observed tens of debris disks at near-infrared wavelengths in both polarized and total intensity as a part of several direct-imaging surveys. Here we discuss the uniform reductions of the J-, H- and K1-band GPI observations, specifically in polarized intensity. This includes 24 debris-disk observations in the H band, 10 debris-disks observations in the J band and 11 disk observations in the K1 band. Additionally, all three reduced data sets have been archived on the digital platform, CANFAR, so that they are available for public use. The purpose of this work is to provide the necessary steps for one to carry out their own data reductions if desired, as well as to create a space where these uniformly reduced data are easily accessible for future analysis and research.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.212
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

Citations0
Published2024
Admission routes1
Has abstractyes

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