Correcting METIS spectra for telluric absorption to maximize spectral fidelity
Bibliographic record
Abstract
METIS is a mid-infrared instrument proposed for the European Extremely Large Telescope. It is designed to provide imaging and spectroscopic capabilities in the 3 - 14 micron region up to a spectral resolution of 100000. One of the novel concepts of METIS is that of a high-resolution integral field spectrograph for a diffraction-limited mid-IR instrument. While this concept has many scientific and operational advantages over a long-slit spectrograph, one drawback is that the spectral resolution changes over the field of view. This has an impact on the procedures to correct for telluric absorption lines imprinted on the science spectra. They are a major obstacle in the quest to maximize spectral fidelity, the ability to distinguish a weak spectral feature from the continuum. The classical technique of division by a standard star spectrum, observed in a single IFS spaxel, cannot simply be applied to all spaxels, because the spectral resolution changes from spaxel to spaxel. Here we present and discuss possible techniques of telluric line correction of METIS IFS spectra, including the application of synthetic model spectra of telluric transmission, to maximize spectral fidelity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".