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Record W2161424626 · doi:10.1088/0004-637x/723/1/457

THE DYNAMICS OF DENSE CORES IN THE PERSEUS MOLECULAR CLOUD. II. THE RELATIONSHIP BETWEEN DENSE CORES AND THE CLOUD

2010· article· en· W2161424626 on OpenAlexaff
Helen Kirk, J. E. Pineda, Doug Johnstone, Alyssa Goodman

Bibliographic record

VenueThe Astrophysical Journal · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsVelocity dispersionPhysicsDispersion (optics)KinematicsMolecular cloudTurbulenceCore (optical fiber)AstrophysicsScale (ratio)Cloud computingLine-of-sightExtinction (optical mineralogy)Length scaleStar formationComputational physicsMechanicsGalaxyClassical mechanicsOpticsStars

Abstract

fetched live from OpenAlex

We utilize the extensive data sets available for the Perseus molecular cloud to analyze the relationship between the kinematics of small-scale dense cores and the larger structures in which they are embedded. The kinematic measures presented here can be used in conjunction with those discussed in our previous work as strong observational constraints that numerical simulations (or analytic models) of star formation should match. We find that dense cores have small motions with respect to the 13 CO gas, about one third of the 13 CO velocity dispersion along the same line of sight. Within each extinction region, the core-to-core velocity dispersion is about half of the total ( 13 CO) velocity dispersion seen in the region. Large-scale velocity gradients account for roughly half of the total velocity dispersion in each region, similar to what is predicted from large-scale turbulent modes following a power spectrum of P ( k ) ∝ k −4 .

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.250
Teacher spread0.239 · 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

Citations48
Published2010
Admission routes1
Has abstractyes

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