A census of quasar-intrinsic absorption in the Hubble Space Telescope archive: systems from high-resolution echelle spectra★
Bibliographic record
Abstract
We present a census of zabs ≲ 2 intrinsic (those showing partial coverage) and associated (zabs ∼ zem) quasar absorption-line systems detected in the Hubble Space Telescope archive of Space Telescope Imaging Spectrograph echelle spectra. This work complements the Misawa et al. survey of 2 < zem < 4 quasars that selects systems using similar techniques. We confirm the existence of so-called strong N v intrinsic systems (where the equivalent width of H i Lyα is small compared to N v λ1238) presented in that work, but find no convincing cases of ‘strong C iv’ intrinsic systems at low redshift/luminosity. Moreover, we also report on the existence of ‘strong O vi’ systems. From a comparison of partial coverage results as a function of ion, we conclude that systems selected by the N v ion have the highest probability of being intrinsic. By contrast, the C iv and O vi ions are poor selectors. Of the 30 O vi systems tested, only two of the systems in the spectrum on 3C 351 show convincing evidence for partial coverage. However, there is an ∼3σ excess in the number of absorbers near the quasar redshift (|Δv| ≤ 5000 km s−1) over absorbers at large redshift differences. In at least two cases, the associated O vi systems are known not to arise close to the accretion disc of the quasar.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".