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Record W4392620441 · doi:10.5194/egusphere-egu24-15544

Large Interferometer for Exoplanets (LIFE): characterizing the mid-infrared thermal emission of terrestrial exoplanets

2024· preprint· en· W4392620441 on OpenAlexaff
Tim Lichtenberg, Sascha P. Quanz, Lena Noack, Daniel Angerhausen, Sarah Rugheimer, Adrian M. Glauser, Jens Kammerer, A. Fortier, Michael Ireland, Denis Defrère, H. Linz, Nicolas Iro

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsYork University
Fundersnot available
KeywordsExoplanetInterferometryInfraredThermal emissionAstrobiologyThermal infraredPhysicsThermalEnvironmental scienceAstronomyPlanetMeteorology

Abstract

fetched live from OpenAlex

The atmospheric characterization of a significant number of terrestrial exoplanets is a major goal of 21st century astrophysics. However, none of the currently adopted missions worldwide has the technical capabilities to achieve this goal. Here we present the LIFE mission concept, which addresses this issue by investigating the scientific potential and technological challenges of an ambitious mission employing a formation-flying nulling interferometer in space working at mid-infrared wavelengths. LIFE, in synergy with other planned future missions, will for the first time in human history enable us to understanding global biosignatures and planetary habitability in the context of the diversity of planetary systems. Breakthroughs in our understanding of the exoplanet population and relevant technologies justify the need, but also the feasibility, for future atmosphere characterization and life detection missions to investigate one of the most fundamental questions of humankind: how frequent and diverse are global biospheres in the galaxy?

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.258
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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