MétaCan
Menu
Back to cohort
Record W6931581060 · doi:10.5281/zenodo.6564346

Detecting Biosignatures of Nearby Rocky Exoplanets: Simulations of High Spectral Resolution Observations with the ELTs

2022· article· en· W6931581060 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
FundersEuropean Commission
KeywordsExoplanetPlanetHabitabilitySpectral resolutionAdaptive opticsAtmosphere (unit)Terrestrial planetHigh resolution

Abstract

fetched live from OpenAlex

The imminent arrival of the Extremely Large Telescopes (ELTs) will finally deliver the observational power capable of assessing the habitability of nearby rocky exoplanets. The ELT presents us with the exciting opportunity of being able to spatially resolve the terrestrial exoplanet Proxima b, which lies in the habitable zone of Proxima Centuri. This would allow molecule mapping, a technique that uses the spatial separation plus cross correlation high resolution spectroscopy to disentangle the planet's spectrum from the host star and characterise its atmosphere. Here we present simulations in reflected light for the High Contrast Adaptive Optics (HCAO) mode of HARMONI/ELT, using model planet spectra from the Carl Sagan Institute designed specifically for Proxima b and its M-dwarf host star. HARMONI's resolution (R=17,385) is well suited to molecule mapping, with access to wavelengths covering multiple biosignatures. Our simulator shows that this first light ELT instrument can characterise the atmosphere of Proxima b, within a very reasonable time frame, but requires intervention on the focal plane masks in HARMONI's current instrument design. If changed, HARMONI has the potential to identify CO2, CH4, and H2O in Proxima b. Our simulator is highly versatile and we are extending to other instruments for the ELTs, including METIS/ELT and GMagAO-X+IFS/GMT.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.233
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207