Bibliographic record
Abstract
The balance of evidence indicates that individual galaxies and groups or clusters of galaxies are embedded in enormous distributions of cold, weakly interacting dark matter. These dark matter “halos” provide the scaffolding for all luminous structures in the universe, and their properties comprise an essential part of the current cosmological model. I review the internal properties of dark matter halos, focussing on the simple universal trends predicted by numerical simulations of structure formation. Simulations indicate that halos should all have roughly the same spherically averaged density profile and kinematic structure and predict simple distributions of shape, formation history, and substructure in density and kinematics, over an enormous range of halo mass and for all common variants of the concordance cosmology. I describe observational progress towards testing these predictions by measuring masses, shapes, profiles, and substructure in real halos using baryonic tracers or gravitational lensing. An important property of simulated halos (possibly the most important property) is their dynamical “age”, or degree of internal relaxation. I review recent gravitational lensing studies of galaxy clusters which will measure substructure and relaxation in a large sample of individual cluster halos, producing quantitative measures of age that are well matched to theoretical predictions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".