Ram pressure stripping candidates in the coma cluster: evidence for enhanced star formation
Bibliographic record
Abstract
ABSTRACT The Coma cluster is the nearest massive ($M \gtrsim 10^{15}\, \mathrm{M_\odot }$) galaxy cluster, making it an excellent laboratory to probe the influence of the cluster environment on galaxy star formation. Here, we present a sample of 41 galaxies with disturbed morphologies consistent with ram pressure stripping. These galaxies are identified visually using high-quality, multiband imaging from the Canada–France–Hawaii telescope covering ${\sim}9\, \mathrm{deg^2}$ of the Coma cluster. These ‘stripping candidates’ are clear outliers in common quantitative morphological measures, such as concentration-asymmetry and Gini-M20, confirming their disturbed nature. Based on the orientations of observed asymmetries, as well as the galaxy positions in projected phase space, these candidates are consistent with galaxies being stripped shortly after infall on to the Coma cluster. Finally, the stripping candidates show enhanced star formation rates, both relative to ‘normal’ star-forming Coma galaxies and isolated galaxies in the field. Ram pressure is likely driving an enhancement in star formation during the stripping phase, prior to quenching. On the whole, ram pressure stripping appears to be ubiquitous across all regions of the Coma cluster.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".