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Record W1678917636

Sub-surface deposits of hydrous silicates or hydrated magnesium sulfates as hydrogen reservoirs near the Martian equator : plausible or not?

2004· paratext· en· W1678917636 on OpenAlexaff
Claire I. Fialips, J. W. Carey, D. T. Vaniman, W. C. Feldman, D. L. Bish, M. T. Mellon

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2004
Typeparatext
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsSt. Clair College
Fundersnot available
KeywordsRegolithMartianMars Exploration ProgramAstrobiologyGeologyMineralogyMartian surface
DOInot available

Abstract

fetched live from OpenAlex

Neutron maps obtained using the neutron spectrometer (NS) and the high-energy neutron detector aboard the Mars Odyssey spacecraft reveal variations in the concentration of hydrogen over the martian low to middle latitudes, with up to {approx}10 wt% water-equivalent hydrogen in some equatorial regions. Infrared spectroscopic data provide evidence of chemically and/or physically bound H{sub 2}O and/or OH. Likewise, the decrease in flux of epithermal neutrons in Arabia Terra and southwest of Olympus Mons has been attributed to enhanced concentration of water-bearing minerals in the subsurface. The near-surface martian regolith is expected to contain both unweathered and weathered materials. It may contain significant and heterogeneously distributed amounts of hydrous minerals, such as clays, zeolites, and/or salt hydrates, such as MgSO{sub 4} {center_dot} nH{sub 2}O. Experimental studies suggest that if such water-bearing minerals formed in the past on the martian surface, they may retain significant amounts of water under present martian surface conditions. Hydrous minerals could thus account for some or all of the water observed in the martian regolith by Odyssey. Our study uses surface P-T data to predict regions of stability and the hydration state of selected water-bearing minerals from low to middle latitudes and to identify the nature and amount of hydrous minerals that could possibly account for the water observed by NS.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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 designTheoretical or conceptual
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

Citations4
Published2004
Admission routes1
Has abstractyes

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