Near-infrared diffuse interstellar bands towards Her 36
Bibliographic record
Abstract
Discovered almost a century ago, the diffuse interstellar bands (DIBs) still lack convincing and comprehensive identification. Hundreds of DIBs have now been observed in the near-ultraviolet (NUV), visible, and near-infrared (NIR). They are widely held to be molecular in origin, and modelling of their band profiles offers powerful constraints on molecular constants. Herschel 36, the illuminating star of the Lagoon Nebula, has been shown to possess unusually broad and asymmetric DIB profiles in the visible, and is also bright enough for NIR observation. We present here high-resolution spectroscopic observations targeting the two best-known NIR DIBs at 11 797.5 and 13 175 Å towards this object and a nearby comparison O-star, 9 Sgr, using the GNIRS instrument on Gemini North. We show a clear detection of the 13 175 Å DIB in both stars, and find (i) that it does not exhibit the unusual wing structure of some of the visual DIBs in Her 36 and (ii) that the depth of the band in the two objects is very similar, also contrary to the behaviour of the visual DIBs. We discuss the implications of these results for multiple DIB carrier candidates, and the location of their carriers along the observed lines of sight.
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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) | 0.003 | 0.002 |
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".