The neutral hydrogen content of Fornax cluster galaxies
Bibliographic record
Abstract
We present a new set of deep Hi observations of member galaxies of the Fornax cluster. We detected 35 cluster galaxies in Hi. The resulting sample, the most comprehensive to date, is used to investigate the distribution of neutral hydrogen in the cluster galaxies. We compare the Hi content of the detected cluster galaxies with that of field galaxies by measuring Hi mass-to-light ratios and the Hi deficiency parameter of Solanes et al. ([CITE]). The mean Hi mass-to-light ratio of the cluster galaxies is , significantly lower than for a sample of Hi-selected field galaxies (), although not as low as in the Virgo cluster (). In addition, the Hi content of two cluster galaxies (NGC 1316C and NGC 1326B) appears to have been affected by interactions. The mean Hi deficiency for the cluster is (for galaxy types ), significantly greater than for the field sample (). Both these tests show that Fornax cluster galaxies are Hi-deficient compared to field galaxies. The kinematics of the cluster galaxies suggests that the Hi deficiency may be caused by ram-pressure stripping of galaxies on orbits that pass close to the cluster core. We also derive the most complete B-band Tully -Fisher relation of inclined spiral galaxies in Fornax. A subcluster in the South-West of the main cluster contributes considerably to the scatter. The scatter for galaxies in the main cluster alone is 0.50 mag, which is slightly larger than the intrinsic scatter of 0.4 mag. We use the Tully -Fisher relation to derive a distance modulus of Fornax relative to the Virgo cluster of mag. The galaxies in the subcluster are () mag brighter than the galaxies of the main cluster, indicating that they are situated in the foreground. With their mean velocity 95 km s-1 higher than that of the main cluster we conclude that the subcluster is falling into the main Fornax 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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".