The diffuse interstellar band around 8620 Å
Bibliographic record
Abstract
Context. Diffuse interstellar bands (DIBs) are interstellar absorption features that widely exist in the optical and near-infrared wavelength range. DIBs play an important role in the lifecycle of the interstellar medium and can also be used to trace the Galactic structure. Aims. We developed a set of procedures to automatically detect and measure the DIB around 8620 Å (the Gaia DIB) for a wide range of temperatures. The method was tested on ~5000 spectra from the Giraffe Inner Bulge Survey (GIBS) that has a spectral window similar to that of the Gaia–RVS spectra. Based on this sample, we studied the correlation between the equivalent width (EW) of the Gaia DIB and the interstellar reddening E(J − KS) toward the inner Galaxy, as well as the DIB intrinsic properties. Methods. Our procedure automatically checks and eliminates invalid cases, and then applies a specific local normalization. The DIB profile is fit with a Gaussian function. Specifically, the DIB feature is extracted from the spectra of late-type stars by subtracting the corresponding synthetic spectra. For early-type stars we applied a specific model based on the Gaussian process that needs no prior knowledge of the stellar parameters. In addition, we provide the errors contributed by the synthetic spectra and from the random noise. Results. After validation, we obtained 4194 reasonable fitting results from the GIBS database. An EW versus E(J − KS) relation is derived as E(J − KS) = 1.875 (±0.152) × EW − 0.011 (±0.048), according to E(B − V)∕EW = 2.721, which is highly consistent with previous results toward similar sightlines. After a correction based on the Vista Variables in the Via Lactea (VVV) database for both EW and reddening, the coefficient derived from individual GIBS fields, E(J − KS)∕EW = 1.884 ± 0.225, is also in perfect agreement with literature values. Based on a subsample of 1015 stars toward the Galactic center within − 3° < b < 3° and − 6° < l < 3°, we determined a rest-frame wavelength of the Gaia DIB as 8620.55 Å. Conclusions. The procedures for automatic detection and measurement of the Gaia DIB are successfully developed and have been applied to the GIBS spectra. A Gaussian profile is proved to be a proper and stable assumption for the Gaia DIB as no intrinsic asymmetry is found. A tight linearity of its correlation with the reddening is derived toward the inner Milky Way, which is consistent with previous results.
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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 | 0.000 |
| 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".