<i>HST</i> viewing of spectacular star-forming trails behind ESO 137-001
Bibliographic record
Abstract
ABSTRACT We present the results from the HST WFC3 and ACS data on an archetypal galaxy undergoing ram pressure stripping (RPS), ESO 137-001, in the nearby cluster Abell 3627. ESO 137-001 is known to host a prominent stripped tail detected in many bands from X-rays, H α to CO. The HST data reveal significant features indicative of RPS such as asymmetric dust distribution and surface brightness as well as many blue young star complexes in the tail. We study the correlation between the blue young star complexes from HST, H ii regions from H α (MUSE), and dense molecular clouds from CO (ALMA). The correlation between the HST blue star clusters and the H ii regions is very good, while their correlation with the dense CO clumps are typically not good, presumably due in part to evolutionary effects. In comparison to the starburst99 + cloudy model, many blue regions are found to be young (<10 Myr) and the total star formation (SF) rate in the tail is 0.3–0.6 M⊙ yr−1 for sources measured with ages less than 100 Myr, about 40 per cent of the SF rate in the galaxy. We trace SF over at least 100 Myr and give a full picture of the recent SF history in the tail. We also demonstrate the importance of including nebular emissions and a nebular to stellar extinction correction factor when comparing the model to the broad-band data. Our work on ESO 137-001 demonstrates the importance of HST data for constraining the SF history in stripped tails.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".