Early-type stars observed in the ESO UVES Paranal Observatory Project – IV. Studies of CN, CH+ and CH in the interstellar medium
Bibliographic record
Abstract
High spectral resolution (∼80 000) and signal-to-noise observations from the Ultraviolet and Visual Echelle Spectrograph Paranal Observatory Project (UVES-POP) are used to study the interstellar molecular lines CN (3874 Å), CH+ (3957, 4232 Å) and CH (3886, 4300 Å) towards 74 O- and B-type stellar sightlines. Additionally, archive data are presented for 140 ELODIE early-type stellar sightlines at R = 42 000, plus 25 FEROS at R = 48 000 and 3 UVES at R > 50 000, mainly in the CH+ (4232 Å) and CH (3886, 4300 Å) transitions. Detection rates are ∼45 per cent for CN and ∼67 per cent for the other lines in the POP sample, and ∼10–15 per cent for CH+ and CH lines in the additional sample. CH and CH+ are well correlated between log[N(CH) cm−2]∼12–14, implying that these clouds are CH+-like CH and not CN-like CH. CH is also very well correlated with Na i D in the range log[N(Na i cm−2]) ∼12.2–14.2. A few sightlines show tentative velocity shifts of ∼2 km s−1 between CH and CH+, which appear to be caused by differences in component strength in blends, and hence do not provide firm evidence for shocks. Finally, we describe a search for 13CH+ in a sightline towards HD 76341. No 13CH+ is detected, placing a limit on the 13CH+ to 12CH+ ratio of ∼0.01. If a formal fit is attempted, the equivalent width ratio in the two isotopes is a factor ∼90 but with large errors.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".