Detectability of Atmospheric Climate and Biosignatures with the Large Interferometer for Exoplanets (LIFE) for terrestrial-type Exoplanets
Bibliographic record
Abstract
ABSTRACT We investigate the detectability of atmospheric biosignatures with the Large Interferometer for Exoplanets (LIFE) mission. Starting with the modern Earth we model the climate, photochemistry, and spectra of Earth-like planets over a range of insolation, gravity, humidity, albedo, atmospheric mass, and carbon dioxide abundances, and investigate detectability of key atmospheric species by LIFE for Earth-like planets assumed to lie at 10 pc for the LIFE (20-d viewing) baseline case. We find that atmospheric ozone (O3) abundances are maintained over a range of conditions. The O3 fundamental band is visible for most scenarios studied but is weakened for exoplanets with cooler central stars. Additional potential biosignatures such as methane (CH4), nitrous oxide (N2O), and chloromethane (CH3Cl) have larger abundances for low UV conditions e.g. exoplanets orbiting cooler central stars or having strong atmospheric shielding. Regarding spectral signatures, CH4 and water (H2O) signals from 6–8 μm are evident in most scenarios, as is the carbon dioxide (CO2) 15 μm band, which strengthens for low-O2 scenarios associated with upper atmosphere cooling. Considering a 20-d viewing, H2O is retrievable with a confidence level (CL) of 3.6σ for an Earth-like planet orbiting a cool star. N2O is not observable with a CL sigma mostly less than one for the scenarios considered. CH4 features a CL sigma detectability range of up to 1.5. O3 is detectable in most cases with a CL of ~2.0 to 3.0 (including the low-ozone Proterozoic) except for the extremely low O3 Archaean scenario and the low-pressure atmosphere scenario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".