The Massively Accreting Cluster A2029
Bibliographic record
Abstract
Abstract We explore the structure of galaxy cluster A2029 and its surroundings based on intensive spectroscopy along with X-ray and weak lensing observations. The redshift survey includes 4376 galaxies (1215 spectroscopic cluster members) within 40′ of the cluster center; the redshifts are included here. Two subsystems, A2033 and a southern infalling group (SIG), appear in the infall region based on the spectroscopy, as well as on the weak lensing and X-ray maps. The complete redshift survey of A2029 also identifies at least 12 foreground and background systems (10 are extended X-ray sources) in the A2029 field; we include a census of their properties. The X-ray luminosities ( L X )–velocity dispersions ( ) scaling relations for A2029, A2033, SIG, and the foreground/background systems are consistent with the known cluster scaling relations. The combined spectroscopy, weak lensing, and X-ray observations provide a robust measure of the masses of A2029, A2033, and SIG. The total mass of the infalling groups (A2033 and SIG) is ∼60% of the M 200 of the primary cluster, A2029. Simple dynamical considerations suggest that A2029 will accrete these subsystems in the next few Gyr. In agreement with simulations and other clusters observed in a similar redshift range, the total mass in the A2029 infall region is comparable to the A2029 M 200 and will mostly be accreted in the long-term future.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".