The <scp>XXL</scp> survey: First results and future
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The XXL survey currently covers two 25 deg 2 patches with XMM observations of ∼10 ks. We summarize the scientific results associated with the first release of the XXL dataset, which occurred in mid‐2016. We review several arguments for increasing the survey depth to 40 ks during the next decade of XMM operations. X‐ray ( z < 2) cluster, ( z < 4) active galactic nuclei ( AGN ), and cosmic background survey science will then benefit from an extraordinary data reservoir. This, combined with deep multi‐ λ observations, will lead to solid standalone cosmological constraints and provide a wealth of information on the formation and evolution of AGN , clusters, and the X‐ray background. In particular, it will offer a unique opportunity to pinpoint the z > 1 cluster density. It will eventually constitute a reference study and an ideal calibration field for the upcoming eROSITA and Euclid missions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it