Bibliographic record
Abstract
Using new photometric and spectroscopic data in the fields of nine strong gravitational lenses that lie in galaxy groups, we analyze the effects of both the local group environment and line-of-sight galaxies on the lens potential. We use Monte Carlo simulations to derive the shear directly from measurements of the complex lens environment, providing the first detailed independent check of the shear obtained from lens modeling. We account for possible tidal stripping of the group galaxies by varying the fraction of total mass apportioned between the group dark matter halo and individual group galaxies. The environment produces an average shear of gamma = 0.08 (ranging from 0.02 to 0.17), significant enough to affect quantities derived from lens observables. However, the direction and magnitude of the shears do not match those obtained from lens modeling in three of the six 4-image systems in our sample (B1422, RXJ1131, and WFI2033). The source of this disagreement is not clear, implying that the assumptions inherent in both the environment and lens model approaches must be reconsidered. If only the local group environment of the lens is included, the average shear is gamma = 0.05 (ranging from 0.01 to 0.14), indicating that line-of-sight contributions to the lens potential are not negligible. We isolate the effects of various theoretical and observational uncertainties on our results. Of those uncertainties, the scatter in the Faber-Jackson relation and error in the group centroid position dominate. Future surveys of lens environments should prioritize spectroscopic sampling of both the local lens environment and objects along the line of sight, particularly those bright (I < 21.5) galaxies projected within 5' of the lens.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".