A SENSITIVE SPECTRAL SURVEY OF INTERSTELLAR FEATURES IN THE NEAR-UV [3050-3700 Å]
Bibliographic record
Abstract
We present a comprehensive and sensitive unbiased survey of interstellar features in the near-UV range (3050–3700 Å). We combined a large number of VLT/UVES archival observations of a sample of highly reddened early-type stars—typical diffuse interstellar band targets—and unreddened standards. We stacked the individual observations to obtain a reddened "superspectrum" in the interstellar rest frame with a signal-to-noise ratio exceeding 1500. We compared this to the analogous geocentric and stellar rest frame superspectra as well as to an unreddened superspectrum to find interstellar absorption features. We find 30 known features (11 atomic and 19 molecular) and tentatively detect up to 7 new interstellar absorption lines of unknown origin. Our survey is sensitive to narrow and weak features; telluric residuals preclude us from detecting broader features. For each sightline, we measured fundamental parameters (radial velocities, line widths, and equivalent widths) of the detected interstellar features. We also revisit upper limits for the column densities of small, neutral polycyclic aromatic hydrocarbon molecules that have strong transitions in this wavelength range.
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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 | 0.003 | 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) | 0.001 | 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".