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Record W4416196922 · doi:10.3847/psj/ae1579

Seasonal Effects of the Changing Photon Scattering Rates on Mercury’s Exospheric Structure

2025· article· en· W4416196922 on OpenAlexfundno aff
M. Bürger, R. M. Killen, Ronald J. Vervack, Orenthal J. Tucker, Liam S. Morrissey, D. W. Savin

Bibliographic record

VenueThe Planetary Science Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExosphereScatteringRadiation pressurePhotonIonizationRadiation

Abstract

fetched live from OpenAlex

Abstract Emission in Mercury’s exosphere observed from the ground and by spacecraft is produced by resonant scattering of sunlight. The process of resonant scattering changes the structure of the exosphere owing to the transfer of momentum between the incident photons and the scattering atoms, resulting in a net antisunward-directed force known as radiation pressure. The photon scattering rate (the so-called g -value) and the magnitude of radiation pressure depend strongly on both Mercury’s distance from the Sun and the radial velocities of the scattering atoms relative to the Sun. We discuss four effects of the changing g -value over a Mercury year that require a model capable of tracking the positions and speeds of exospheric constituents in order to properly interpret emission data: (1) variations in the escape flux of atoms, (2) variations in the ratio of atoms that escape Mercury in neutral versus ionized form, (3) difficulties in determining where material was ejected from the surface based on the locations of the emitting atoms in the exosphere, and (4) systematic uncertainties in interpreting the column density of emitting gas using a constant g -value versus a variable g -value that takes into account the radial motion of the atoms relative to the Sun.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.213
Teacher spread0.207 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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