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Hollow locations within impact craters of different degradation stages on Mercury

2025· article· W4417281565 on OpenAlexaff
Elisabeth Giroud-Proeschel, C. L. Johnson, M. Jellinek, F. M. Rossmann

Bibliographic record

Venuenot available
Typearticle
Language
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImpact craterMercury (programming language)Degradation (telecommunications)Earth surface

Abstract

fetched live from OpenAlex

Hollows are shallow, irregular-shaped depressions on the surface of Mercury, often surrounded by bright halos, frequently associated with impact craters, that form via the loss of crustal volatiles. Here, we use and supplement existing data sets of hollows to investigate the type locations (wall, floor, intersection, central structure, superposed craters, proximal ejecta) at which hollows occur within impact craters with a degradation class. We find that hollows within fresh host craters are distributed among all type locations, whereas hollows within degraded host craters occur primarily within superposed craters. However, most superposed craters within degraded hosts do not have hollows. Our results suggest that the cratering process, that forms either host or superposed craters, drives hollow formation, and successively depletes hollow-forming material reservoirs as the host crater degrades. Additionally, hollows occur within superposed craters of all diameters, suggesting that hollow-forming material is an inherent component of Mercury’s upper crust.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.269
Teacher spread0.252 · 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
Published2025
Admission routes1
Has abstractyes

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