[no title]
Bibliographic record
Abstract
We present weak lensing data from the Hubble Space Telescope(HST)/Space Telescope A901/902 Galaxy Evolution Survey (STAGES) survey to study the three-dimensional spatial distribution of matter and galaxies in the Abell 901/902 supercluster complex. Our method improves over the existing 3D lensing mapping techniques by calibrating and removing redshift bias and accounting for the effects of the radial elongation of 3D structures. We also include the first detailed noise analysis of a 3D lensing map, showing that even with deep HST-quality data, only the most massive structures, for example M200≳ 1015 M&sun; h-1 at z˜ 0.8, can be resolved in 3D with any reasonable redshift accuracy (Δz≈ 0.15). We compare the lensing map to the stellar mass distribution and find luminous counterparts for all mass peaks detected with a peak significance >3σ. We see structures in and behind the z= 0.165 foreground supercluster, finding structure directly behind the A901b cluster at z˜ 0.6 and also behind the south-west (SW) group at z˜ 0.7. This 3D structure viewed in projection has no significant impact on recent mass estimates of A901b or the SW group components SWa and SWb.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".