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Record W4404862339 · doi:10.1029/2024gl111183

Iridescence Reveals the Formation and Growth of Ice Aerosols in Martian Noctilucent Clouds

2024· article· en· W4404862339 on OpenAlexaff
M. T. Lemmon, Á. Vicente‐Retortillo, Scott D. Guzewich, Manuel de la Torre Juárez, A. C. Innanen, Charissa Campbell, J. N. Maki, M. C. Malin, John E. Moores

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
FundersAgencia Estatal de InvestigaciónMinisterio de Ciencia e InnovaciónCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsMartianAstrobiologyIridescenceAtmospheric sciencesGeologyMars Exploration ProgramPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract Water and carbon dioxide each form mesospheric clouds on Mars. At such altitudes (40–100 km), clouds may remain sunlit for part of the night. We describe a previously unreported, visually spectacular season of iridescent, noctilucent clouds visible in early southern autumn from the Curiosity rover's site in Gale crater. Ice nucleation begins near sunset with a narrow range of particle sizes, and the ice aerosols grow and precipitate. The iridescence, visible through three‐color imaging, arises from locally uniform particle sizes resulting from similar growth histories. Colorful fall streaks show the clouds evolving, and a scattering corona shows size uniformity over large areas. The terminator was observed on the clouds, allowing the determination of cloud altitudes and a likely CO 2 composition. This is the first observation of particle size variations within individual Martian clouds, allowing a new probe of Martian cloud physics.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.034
GPT teacher head0.299
Teacher spread0.265 · 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 designObservational
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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