Telluric absorption lines in the ALMA spectra of η Car
Bibliographic record
Abstract
ABSTRACT The massive binary system formed by η Car and an unknown companion is a strong source at millimetre and submillimetre wavelengths. Close to the stars, continuum bremsstrahlung and radio recombination lines originate in the massive ionized wind of η Car and in several compact sources of high density plasma. Molecular lines are also detected at these wavelengths, some of them are seen in absorption towards the continuum emission region, many of them revealed by ALMA observations. However, because the ALMA atmospheric calibration is performed in a low spectral resolution mode, telluric lines can still be present in some high-resolution spectra of scientific products, which could lead to a false identification of molecules. In this work, we explore three different sets of ALMA archive data of η Car, including high resolution (0.065 arcsec × 0.043 arcsec) observations recently published by our group, to verify which of these absorption lines are real and discuss their origin. We conclude that some of them truly originate in clouds close to the binary system, while others are artefacts of a faulty elimination of telluric lines during ALMA calibration procedure. We found that these absorption lines are not present in the phase calibrators because they are much weaker than η Car, where the absorption line appears because the high intensity continuum enhances the small individual systematic calibration 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".