Unveiling the Galaxy Cluster - Cosmic Web Connection with X-ray\n observations in the Next Decade
Bibliographic record
Abstract
In recent years, the outskirts of galaxy clusters have emerged as one of the\nnew frontiers and unique laboratories for studying the growth of large scale\nstructure in the universe. Modern cosmological hydrodynamical simulations make\nfirm and testable predictions of the thermodynamic and chemical evolution of\nthe X-ray emitting intracluster medium. However, recent X-ray and\nSunyaev-Zeldovich effect observations have revealed enigmatic disagreements\nwith theoretical predictions, which have motivated deeper investigations of a\nplethora of astrophysical processes operating in the virialization region in\nthe cluster outskirts. Much of the physics of cluster outskirts is\nfundamentally different from that of cluster cores, which has been the main\nfocus of X-ray cluster science over the past several decades. A next-generation\nX-ray telescope, equipped with sub-arcsecond spatial resolution over a large\nfield of view along with a low and stable instrumental background, is required\nin order to reveal the full story of the growth of galaxy clusters and the\ncosmic web and their applications for cosmology.\n
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".