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Record W2047272174 · doi:10.1086/588725

On the Constancy of the Characteristic Mass of Young Stars

2008· article· en· W2047272174 on OpenAlexaff
Bruce G. Elmegreen, Ralf S. Klessen, C. D. Wilson

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAstrophysicsPhysicsMetallicityStarsStar formationRedshiftMolecular cloudInitial mass functionThermalIonizationFragmentation (computing)GalaxyThermodynamicsIon

Abstract

fetched live from OpenAlex

The characteristic mass M_c in the stellar initial mass function (IMF) is about constant for most star-forming regions. Numerical simulations consistently show a proportionality between M_c and the thermal Jeans mass M_J at the time of cloud fragmentation, but no models have explained how it can be the same in diverse conditions. Here we show that M_J depends weakly on density, temperature, metallicity, and radiation field in three environments: the dense cores where stars form, larger star-forming regions ranging from GMCs to galactic disks, and the interiors of HII regions and super star clusters. In dense cores, the quantity T^{3/2}n^{-1/2} that appears in M_J scales with core density as n^{0.25} or with radiation density as U^{0.1} at the density where dust and gas come into thermal equilibrium. On larger scales, this quantity varies with ambient density as n^{-0.05} and ambient radiation field as U^{-0.033} when the Kennicutt-Schmidt law of star formation determines U(n). In super star clusters with ionization and compression of pre-stellar globules, M_J varies as the 0.13 power of the cluster column density. These weak dependencies on n, U, and column density imply that most environmental variations affect the thermal Jeans mass by at most a factor of ~2. Cosmological increases in M_J, which have been suggested by observations, may be explained if the star formation efficiency is systematically higher at high redshift for a given density and pressure, if dust grains are smaller at lower metallicity, and so hotter for a given radiation field, or if small pre-stellar cores are more severely ionized in extreme starburst conditions.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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 designTheoretical or conceptual
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

Citations103
Published2008
Admission routes1
Has abstractyes

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