The centre-to-limb variations of solar Fraunhofer lines imprinted upon lunar eclipse spectra
Bibliographic record
Abstract
The atmospheres of exoplanets are commonly studied by observing the transit of the planet passing in front of its parent star. The obscuration of part of the stellar disk during a transit will reveal aspects of its surface structure resulting from general centre-to-limb variations (CLVs). These become apparent when forming the ratio between the stellar light in and out of transit. These phenomena can be seen particularly clearly during the progress of a penumbral lunar eclipse, where the Earth transits the solar disk and masks different regions of the solar disk as the eclipse progresses. When inferring the properties of the planetary atmosphere, it is essential that this effect originating at the star is properly accounted for. Using the data observed from the 2014-April-15 lunar eclipse with the ESPaDOnS spectrograph mounted on the Canada France Hawaii Telescope (CFHT), we have obtained for the first time a time sequence of the penumbral spectra. These penumbral spectra enable us to study the centre-to-limb variations of solar Fraunhofer lines when the Earth is transiting Sun. The Na i and Ca ii absorption features reported from previous lunar eclipse observations are demonstrated to be CLV features, which dominate the corresponding line profiles and mask possible planetary signal. Detecting atmospheric species in exoplanets via transit spectroscopy must account for the CLV effect.
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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 | 0.000 |
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".