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Record W2018048585 · doi:10.1088/0004-637x/765/1/59

AN ANALYSIS OF THE DEUTERIUM FRACTIONATION OF STAR-FORMING CORES IN THE PERSEUS MOLECULAR CLOUD

2013· article· en· W2018048585 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsDeuteriumOphiuchusFractionationMolecular cloudStar formationProtostarAstrochemistry

Abstract

fetched live from OpenAlex

We have performed a pointed survey of N 2 D + 2–1 and N 2 D + 3–2 emission toward 64 N 2 H + -bright starless and protostellar cores in the Perseus molecular cloud using the Arizona Radio Observatory Submillimeter Telescope and Kitt Peak 12 m telescope. We find a mean deuterium fractionation in N 2 H + , R D = N (N 2 D + )/ N (N 2 H + ), of 0.08, with a maximum R D = 0.2. In detected sources, we find no significant difference in the deuterium fractionation between starless and protostellar cores, nor between cores in clustered or isolated environments. We compare the deuterium fraction in N 2 H + with parameters linked to advanced core evolution. We only find significant correlations between the deuterium fraction and increased H 2 column density, as well as with increased central core density, for all cores. Toward protostellar sources, we additionally find a significant anticorrelation between R D and bolometric temperature. We show that the Perseus cores are characterized by low CO depletion values relative to previous studies of star-forming cores, similar to recent results in the Ophiuchus molecular cloud. We suggest that the low average CO depletion is the dominant mechanism that constrains the average deuterium fractionation in the Perseus cores to small values. While current equilibrium and dynamic chemical models are able to reproduce the range of deuterium fractionation values we find in Perseus, reproducing the scatter across the cores requires variation in parameters such as the ionization fraction or the ortho-to-para-H 2 ratio across the cloud, or a range in core evolution timescales.

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 score0.013
Threshold uncertainty score0.027

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 science0.0000.000
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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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

Citations24
Published2013
Admission routes1
Has abstractyes

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