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Record W1538635073 · doi:10.1029/2012gl051472

Observations of Mercury's northern cusp region with MESSENGER's Magnetometer

2012· article· en· W1538635073 on OpenAlexaff
R. M. Winslow, C. L. Johnson, B. J. Anderson, H. Korth, J. A. Slavin, Michael E. Purucker, Sean C. Solomon

Bibliographic record

VenueGeophysical Research Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMagnetospherePhysicsSolar windGeophysicsInterplanetary magnetic fieldMagnetometerCusp (singularity)MagnetopauseMercury's magnetic fieldMagnetic fieldAstrophysicsAtmospheric sciencesGeometry

Abstract

fetched live from OpenAlex

The magnetic cusp of a planetary magnetosphere allows solar wind plasma to gain access to the planet's magnetosphere and, for Mercury, the surface. From measurements by the MESSENGER Magnetometer we have characterized the magnetic field in the northern cusp region of Mercury. The first six months of orbital measurements indicate a mean latitudinal extent of the cusp of ∼11°, and a mean local time extent of 4.5 hrs, at spacecraft altitudes. From the average magnetic pressure deficit in the cusp, we estimate that (1.1 ± 0.6) × 10 24 protons s −1 bombard the surface over an area of (5.2 ± 1.6) × 10 11 m 2 near the northern cusp. Plasma pressures in the cusp are 40% higher when the interplanetary magnetic field (IMF) is anti‐sunward than when it is sunward. The influence of the IMF direction does not overcome the north‐south asymmetry of Mercury's internal field, and particle flux to the surface near the southern cusp is predicted to be a factor of 4 greater than in the north. The higher particle flux impacting the surface in the south should lead to a greater exospheric source from the south and a higher rate of space weathering than in the area of the northern cusp.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

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 head0.070
GPT teacher head0.296
Teacher spread0.226 · 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

Citations95
Published2012
Admission routes1
Has abstractyes

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