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Record W1997700621 · doi:10.1086/521041

Modeling Lyman Continuum Emission from Young Galaxies

2007· article· en· W1997700621 on OpenAlexaff
Alexei O. Razoumov, Jesper Sommer‐Larsen

Bibliographic record

VenueThe Astrophysical Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPhysicsAstrophysicsRedshiftGalaxyAstronomyStar formationLuminous infrared galaxyGalaxy formation and evolution

Abstract

fetched live from OpenAlex

Based on cosmological simulations, we model Lyman continuum emission from a sample of 11 high-redshift star-forming galaxies spanning a mass range of a factor 20. Each of the 11 galaxies has been simulated both with a Salpeter and a Kroupa initial mass function (IMF). We find that the Lyman continuum luminosity of an average star-forming galaxy in our sample declines from z = 3.6 to 2.4 due to the steady gas infall and higher gas clumping at lower redshifts, increasingly hampering the escape of ionizing radiation. The galaxy-to-galaxy variation of apparent Lyman continuum emission at a fixed redshift is caused in approximately equal parts by the intrinsic variations in the Lyman continuum emission and by orientation effects. The combined scatter of an order of magnitude can explain the variance in the far-UV spectra of high-redshift galaxies detected by Shapley and coworkers. Our results imply that the cosmic galactic ionizing UV luminosity is monotonically decreasing from z = 3.6 to 2.4, curiously anticorrelated with the star formation rate in the smaller galaxies, which on average rises during this redshift interval.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Citations32
Published2007
Admission routes1
Has abstractyes

Explore more

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