MétaCan
Menu
Back to cohort
Record W2790779039 · doi:10.1002/2017gl072652

Submicroscopic metallic iron in lunar soils estimated from the in situ spectra of the Chang'E‐3 mission

2017· article· en· W2790779039 on OpenAlexaff
Zhenchao Wang, Yunzhao Wu, D. T. Blewett, E. A. Cloutis, Yongchun Zheng, Jun Chen

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Winnipeg
FundersNational Natural Science Foundation of China
KeywordsRegolithSpace weatheringLunar soilRocket (weapon)Maturity (psychological)WeatheringSpectral lineMetalGeologySoil waterAtmospheric radiative transfer codesRadiative transferEnvironmental scienceMaterials scienceMineralogyAstrobiologyOpticsPhysicsGeochemistryAstronomyMetallurgySoil science

Abstract

fetched live from OpenAlex

Abstract Submicroscopic metallic iron (SMFe) created by space weathering has strong effects on the optical properties of the lunar surface. Spectra measured in situ by the visible‐near‐infrared spectrometer (VNIS) on board the Chang'E‐3 Yutu rover were used to investigate optical maturity differences at the CE‐3 landing site caused by lander exhaust. SMFe abundances were estimated using Hapke's radiative transfer model. Analysis of the spectrum for a minimally disturbed soil indicates that it contains 0.368 wt % SMFe, corresponding to an I s /FeO maturity index of ~53 and indicating that the landing site is submature. The soil at a location that was more disturbed contains 0.217 wt % SMFe, suggesting that the material removed by the rocket blast is more weathered than the regolith that remained behind. We conclude that maturity differences related to removal of the finest, highly mature particles play a major role in the observed reflectance changes associated with rocket blast.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.336
Teacher spread0.272 · 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 teacher head, 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

Citations40
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicPlanetary Science and ExplorationFrench-language works237,207