A simulated<i>τ</i>CDM cosmology cluster catalogue: the NFW profile and the temperature-mass scaling relations
Bibliographic record
Abstract
We have extracted over 400 clusters, covering more than two decades in mass, from three simulations of the τCDM cosmology. This represents the largest uniform catalogue of simulated clusters ever produced. The clusters exhibit a wide variety of density profiles. Only a minority are well-fitted in their outer regions by the widely used density profile of Navarro, Frenk & White (NFW), which is applicable to relaxed haloes. Others have steeper outer density profiles, show sharp breaks in their density profiles, or have significant substructure. If we force a fit to the NFW profile, then the best-fitting concentrations decline with increasing mass, but this is driven primarily by an increase in substructure as one moves to higher masses. The temperature—mass relations for properties measured within a sphere enclosing a fixed overdensity all follow the self-similar form, T∝M2/3; however, the normalization is lower than the value inferred for observed clusters. The temperature—mass relations for properties measured within a fixed physical radius are significantly steeper then this. Both can be accurately predicted using the NFW model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".