GGSL in galaxy clusters: simulations and lens models
Bibliographic record
Abstract
The dataset contains the snapshots and the subhalo catalogs of the cluster simulations used in the Science publication "An excess of small-scale gravitational lenses observed in galaxy clusters" by Meneghetti et al. (2020). It also contains the lens models (distributed as Lenstool parameter files) of the galaxy clusters used in the comparison to the simulations. More details about the simulations can be found in the papers by E. Rasia, et al. (Astrophys. J.l 813, L17, 2015) and S. Planelles, et al. (Mon. Not. R. Astron. Soc. 467, 3827, 2017). The lens models are discussed in the papers by P. Bergamini, et al. (Astron. Astrophys. 631, A130, 2019) and G. B. Caminha, et al. (Astron. Astrophys. 632, A36, 2019).
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.
How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".