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Record W3176070837 · doi:10.3847/2041-8213/ac0d59

AGB Interlopers in YSO Catalogs Hunted out by NEOWISE

2021· article· en· W3176070837 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
FundersNational Research Foundation of Korea
KeywordsMaserYoung stellar objectStarsInfraredAsymptotic giant branchStellar evolutionVariable star

Abstract

fetched live from OpenAlex

Abstract Asymptotic giant branch stars (AGBs) and young stellar objects (YSOs) often share the same domains in infrared (IR) color–magnitude or color–color diagrams leading to potential misclassification. We extracted a list of AGB interlopers from the published YSO catalogs using the periodogram analysis on the Near-Earth Object Wide Infrared Survey Explorer (NEOWISE) time series data. YSO IR variability is typically stochastic and linked to episodic mass accretion. Furthermore, most variable YSOs are at an early evolutionary stage, with significant surrounding envelope and/or disk material. In contrast, AGBs are often identified by a well-defined sinusoidal variability with periods of a few hundreds days. From our periodogram analysis of all known low-mass YSOs in the Gould Belt, we find 85 AGB candidates, out of which 62 were previously classified as late-stage Class III YSOs. Most of these new AGB candidates have similar IR colors to O-rich AGBs. We observed 73 of these AGB candidates in the H2O, CH3OH, and SiO maser lines to further reveal their nature. The SiO maser emission was detected in 10 sources, confirming them as AGBs because low-mass YSOs, especially Class III YSOs, do not show such maser emission. The H2O and CH3OH maser lines were detected in none of our targets.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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