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Record W1482192333

Comparing Giant Molecular Clouds in M31, M33 & the Milky Way

2000· preprint· en· W1482192333 on OpenAlexaff
Kartik Sheth, S. N. Vogel, C. D. Wilson, T. M. Dame

Bibliographic record

VenuearXiv (Cornell University) · 2000
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMilky WayMolecular cloudSpiral galaxyPhysicsGalaxyAstrophysicsLocal GroupSurface brightnessCloud computingAstronomyDwarf galaxyStars
DOInot available

Abstract

fetched live from OpenAlex

We present new observations of a 2' field in the north-eastern spiral arm of M31. In the 0.8 x 3.6 kpc mosaicked region, we have detected six distinct, large complexes of molecular gas, most of which lie along the spiral arm dust lane or in the vicinity of HII regions. The mean properties of these complexes are as follows: diameter ~ 57+/-13 pc, fwhm velocity ~ 6.5+/-1.2 km/s, M(CO) ~ 3.0+/-1.6 x 10^5 solar masses, peak brightness temperatures ~ 1.6--4.2 K. We investigate the effects of spatial filtering on the quantitative comparison of Local Group and Milky Way giant molecular clouds properties and distributions. We also discuss different cloud identification techniques and their impact on derived cloud properties. When we employ the same cloud identification method and account for differences in data acquisition for M31, Milky Way, and M33, we find that the molecular cloud complexes in all three galaxies are similar. While the global distribution of molecular gas may vary from galaxy to galaxy, cloud complexes are similar, suggesting that cloud formation and destruction is determined by local physics. This work is supported by grants AST-9613716 & AST-9981289 from the National Science Foundation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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

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 head0.042
GPT teacher head0.182
Teacher spread0.141 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

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