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Record W2017701380 · doi:10.1086/499582

Formation of Minigalaxies in Defunct Cosmological H<scp>ii</scp>Regions

2006· article· en· W2017701380 on OpenAlexaff
Sergey Mashchenko, H. M. P. Couchman, Alison Sills

Bibliographic record

VenueThe Astrophysical Journal · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhysicsAstrophysicsRedshiftStar formationGalaxy formation and evolutionGalaxyVirial theoremUniverseQuasarAstronomy

Abstract

fetched live from OpenAlex

Using a large set of high-resolution numerical simulations incorporating nonequilibrium molecular hydrogen chemistry and a constant source of external radiation, we study gas collapse in previously photoionized minigalaxies with virial temperatures less than 10 4 K in the early universe (redshifts z = 10-20). We confirm that the mechanism of positive feedback of ionizing radiation on star formation in minigalaxies proposed by Ricotti and coworkers can be efficient despite a significant flux of metagalactic photodissociating radiation. We derive critical fluxes for the Lyman-Werner background radiation sufficient to prevent the collapse of gas in minigalaxies as a function of the virial mass of the halo and redshift. In our model, the formation of minigalaxies in defunct H II regions is most efficient at large redshifts ( z ≳ 15) and/or for large local gas overdensity δ ≳ 10. We show that nonequilibrium chemistry plays an important dynamical role not only during the initial evolutionary phase, leading to the gas becoming gravitationally unstable inside the minihalo, but also at the advanced stages of the core collapse, resulting in efficient gas accretion in the core region. We speculate on a possible connection between our objects and metal-poor globular clusters and dwarf spheroidal galaxies.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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 designSimulation or modeling
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

Citations9
Published2006
Admission routes1
Has abstractyes

Explore more

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