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Dust emissivity in the star-forming filament OMC 2/3

2022· article· en· W3104349551 on OpenAlexaff
Sarah Sadavoy, Amelia M. Stutz, Scott Schnee, Brian Mason, James Di Francesco, Rachel Friesen

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoNational Research Council CanadaUniversity of Victoria
Fundersnot available
KeywordsEmissivityAstrophysicsProtein filamentBETA (programming language)PhysicsWavelengthSpectral indexAstronomySpectral lineMaterials scienceOptics

Abstract

fetched live from OpenAlex

We present new measurements of the dust emissivity index, β, for the high-mass, star-forming OMC 2/3 filament. We combined 160−500 μm data from Herschel with long-wavelength observations at 2 mm and fit the spectral energy distributions across a ≃2 pc long, continuous section of OMC 2/3 at 15 000 AU (0.08 pc) resolution. With these data, we measured β and reconstructed simultaneously the filtered-out large-scale emission at 2 mm. We implemented both variable and fixed values of β, finding that β = 1.7−1.8 provides the best fit across most of OMC 2/3. These β values are consistent with a similar analysis carried out with filtered Herschel data. Thus, we show that β values derived from spatial filtered emission maps agree well with those values from unfiltered data at the same resolution. Our results contradict the very low β values (~0.9) previously measured in OMC 2/3 between 1.2 mm and 3.3 mm data, which we attribute to elevated fluxes in the 3.3 mm observations. Therefore, we find no evidence of rapid, extensive dust grain growth in OMC 2/3. Future studies with Herschel data and complementary ground-based long-wavelength data can apply our technique to obtain reliable determinations of β in nearby cold molecular clouds.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations38
Published2022
Admission routes1
Has abstractyes

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Same venueSpringer Link (Chiba Institute of Technology)Same topicAstrophysics and Star Formation StudiesFrench-language works237,207