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Record W4390885564 · doi:10.1038/s41550-023-02185-5

Detection of apatite in ferroan anorthosite indicative of a volatile-rich early lunar crust

2024· article· en· W4390885564 on OpenAlexaff
Tara S. Hayden, Thomas J. Barrett, M. Anand, Martin J. Whitehouse, Heejin Jeon, X. Zhao, I. A. Franchi

Bibliographic record

VenueNature Astronomy · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern University
FundersScience and Technology Facilities CouncilVetenskapsrådetNuclear Safety and Security CommissionUniversities Space Research AssociationSolar System Exploration Research Virtual InstituteNational Aeronautics and Space Administration
KeywordsAnorthositeGeologyCrustPlagioclaseGeology of the MoonGeochemistryApatiteMeteoriteMagmaAstrobiologyBasaltPaleontologyVolcano

Abstract

fetched live from OpenAlex

Abstract Determination of the systematics of volatile elements (for example, H, Cl, S) of the early Moon is one of the main objectives of lunar science. This has been hindered by the lack of the main volatile-bearing mineral, apatite, in ferroan anorthosites (FANs), which are thought to represent the primary products of the lunar magma ocean and the earliest lunar crust. Due to the absence of apatite, plagioclase and bulk samples of the FAN suite have been previously utilized for the studies of volatiles in samples representing the earliest-formed lunar crust. Here we provide evidence of apatite in a FAN clast in the lunar meteorite Arabian Peninsula 007. We report that Arabian Peninsula 007 has an ancient age, comparable to those of Apollo FAN samples, with lighter hydrogen (δD = −45‰) and heavier chlorine (δ37Cl = +44‰) isotopic compositions than FAN bulk and plagioclase data. These results suggest that the early lunar crust was significantly more volatile rich than previously thought.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 communication0.0010.000
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 head0.005
GPT teacher head0.222
Teacher spread0.218 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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