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Record W2330444347 · doi:10.1017/s1743921314010540

The Distribution of Mass in (Disk) Galaxies: Maximal or Not?

2014· article· en· W2330444347 on OpenAlexaff
Stéphane Courteau

Bibliographic record

VenueProceedings of the International Astronomical Union · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsQueen's University
FundersScience and Technology Facilities Council
KeywordsPhysicsAstrophysicsDark matter haloGalaxyDark matterAstronomyBaryonGalaxy formation and evolutionDiscDark galaxyCold dark matterGalaxy groupHalo

Abstract

fetched live from OpenAlex

Abstract The relative distribution of matter in galaxies ought to be one of the most definitive predictions of galaxy formation models yet its validation is challenged by numerous observational, theoretical, and operational challenges. All galaxies are believed to be dominated by an invisible matter component in their outskirts. A debate has however been blazing for the last two decades regarding the relative fraction of baryons and dark matter in the inner parts of galaxies: whether galaxies are centrally dominated by baryons (“maximal disk”) is of issue. Some of those debates have been misconstrued on account of operational confusion, such as dark matter fractions being measured and compared at different radii. All galaxies are typically baryon-dominated (maximal) at the center and dark-matter dominated (sub-maximal) in their outskirts; for low-mass galaxies (Vtot ≲ 200 km s− 1), the mass of the dark halo equals the stellar mass at least within 2 disk scale lengths, the transition occurs at larger effective radii for more massive galaxies. An ultimate goal for galaxy structure studies is to achieve accurate data-model comparisons for the relative fractions of baryonic to total matter at any radius.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
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 head0.203
Teacher spread0.197 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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