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Indications for grain growth and mass decrease in cold dust disks around Classical T Tauri stars in the MBM 12 young association

2003· preprint· en· W6910823215 on OpenAlexaff

Bibliographic record

VenuearXiv (Cornell University) · 2003
Typepreprint
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of TorontoHerzberg Institute of Astrophysics
Fundersnot available
KeywordsT Tauri starStarsOpacityAccretion (finance)Accretion discGrain growthSpectral energy distributionCircumstellar diskLine (geometry)

Abstract

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We report detection of continuum emission at 850 and 450 micron from disks around four Classical T Tauri stars in the MBM 12 (L1457) young association. Using a simple model we infer masses of 0.0014-0.012 M_sun for the disk of LkHa 263 ABC, 0.005-0.021 M_sun for S18 ABab, 0.03-0.18 M_sun for LkHa 264 A, and 0.023-0.23 M_sun for LkHa 262. The disk mass found for LkHa 263 ABC is consistent with the 0.0018 M_sun inferred from the scattered light image of the edge-on disk around component C. Comparison to earlier 13CO line observations indicates CO depletion by up to a factor 300 with respect to dark-cloud values. The spectral energy distributions (SED) suggest grain growth, possibly to sizes of a few hundred micron, but our spatially unresolved data cannot rule out opacity as an explanation for the SED shape. Our observations show that these T Tauri stars are still surrounded by significant reservoirs of cold material at an age of 1-5 Myr. We conclude that the observed differences in disk mass are likely explained by binary separation affecting the initial value. With available accretion rate estimates we find that our data are consistent with theoretical expectations for viscously evolving disks having decreased their masses by ~30%.

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)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.040
GPT teacher head0.177
Teacher spread0.137 · 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
GenreOther

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".

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Citations0
Published2003
Admission routes1
Has abstractyes

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