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Record W2003713232 · doi:10.1029/2009gl041087

Rugged lava flows on the Moon revealed by Earth‐based radar

2009· article· en· W2003713232 on OpenAlexaff
B. A. Campbell, B. R. Hawke, Lynn M. Carter, R. R. Ghent, D. B. Campbell

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLavaGeologyEarth (classical element)AstrobiologyRadarGeophysicsRemote sensingMeteorologyGeodesyVolcanoSeismologyAerospace engineeringGeography

Abstract

fetched live from OpenAlex

Basaltic volcanism is widespread on the lunar nearside, and returned samples suggest that the mare‐forming magmas had low viscosity that led to primarily sheet‐like deposits. New 70‐cm wavelength radar observations that probe several meters beneath the lunar surface reveal differences in mare backscatter properties not explained by age or compositional variations. We interpret areas of high backscatter and high circular polarization ratio in Maria Serenitatis, Imbrium, and Crisium as having an enhanced abundance of decimeter‐scale subsurface rocks relative to typical mare‐forming flows. The 3.5 b.y survival of these differences implies an initial platy, blocky, or ridged lava flow surface layer with thickness of at least 3–5 m. Such rugged morphology might arise from episodic changes in magma effusion rate, as observed for disrupted flood basalt surfaces on the Earth and Mars, very high flow velocities, or increased viscosity due to a number of factors. Significant information on lunar mare eruption conditions may thus be obtained from long‐wavelength radar probing of the shallow subsurface.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.032
GPT teacher head0.286
Teacher spread0.254 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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