MétaCan
Menu
Back to cohort
Record W2269826599 · doi:10.1051/0004-6361/201527805

APOGEE strings: A fossil record of the gas kinematic structure

2016· article· en· W2269826599 on OpenAlexfundno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryYork UniversityCarnegie Mellon UniversityOffice of ScienceJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityHarvard UniversityOhio State UniversityNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityUniversity of ArizonaPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsSubstructureStarsVelocity dispersionKinematicsInterstellar mediumDispersion (optics)Line (geometry)Radial velocity

Abstract

fetched live from OpenAlex

We compare APOGEE radial velocities (RVs) of young stars in the Orion A cloud with CO line gas emission and find a correlation between the two at large scales in agreement with previous studies. However, at smaller scales we find evidence for the presence of a substructure in the stellar velocity field. Using a friends-of-friends approach we identify 37 stellar groups with almost identical RVs. These groups are not randomly distributed, but form elongated chains or strings of stars with five or more members with low velocity dispersion across lengths of 1−1.5 pc. The similarity between the kinematic properties of the APOGEE strings and the internal velocity field of the chains of dense cores and fibers recently identified in the dense interstellar medium is striking and suggests that for most of the Orion A cloud, young stars keep memory of the parental gas substructure where they originated.

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)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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

Citations33
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAstronomy and AstrophysicsSame topicAstrophysics and Star Formation StudiesFrench-language works237,207