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RAMSES-CH: a new chemodynamical code for cosmological simulations

2012· article· en· W2099876653 on OpenAlexaff
C. G. Few, S. Courty, B. K. Gibson, Daisuke Kawata, F. Calura, Romain Teyssier

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsSaint Mary's University
FundersScience and Technology Facilities CouncilAgence Nationale de la Recherche
KeywordsPhysicsAstrophysicsSupernovaGalaxyRadiative coolingStar formationStarsRadiative transferType (biology)Galaxy formation and evolution

Abstract

fetched live from OpenAlex

Abstract We present a new chemodynamical code –ramses-ch– for use in simulating the self-consistent evolution of chemical and hydrodynamical properties of galaxies within a fully cosmological framework. We build upon the adaptive mesh refinement code ramses, which includes a treatment of self-gravity, hydrodynamics, star formation, radiative cooling and supernova feedback, to trace the dominant isotopes of C, N, O, Ne, Mg, Si and Fe. We include the contribution of Type Ia and Type II supernovae, in addition to low- and intermediate-mass asymptotic giant branch stars, relaxing the instantaneous recycling approximation. The new chemical evolution modules are highly flexible and portable, lending themselves to ready exploration of variations in the underpinning stellar and nuclear physics. We apply ramses-ch to the cosmological simulation of a typical L★ galaxy, demonstrating the successful recovery of the basic empirical constraints regarding [α/Fe]–[Fe/H] and Type Ia/II supernova rates.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0000.000

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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 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

Citations50
Published2012
Admission routes1
Has abstractyes

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