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Record W2985232903 · doi:10.1029/2019je005992

Imbrium Age for Zircons in Apollo 17 South Massif Impact Melt Breccia 73155

2019· article· en· W2985232903 on OpenAlexaff
Bidong Zhang, Yangting Lin, D. E. Moser, Jialong Hao, S. R. Shieh, Audrey Bouvier

Bibliographic record

VenueJournal of Geophysical Research Planets · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsWestern University
FundersChina Scholarship Council
KeywordsGeologyGeochemistryBrecciaMassifApolloProvenanceEjectaPetrology

Abstract

fetched live from OpenAlex

Abstract The Apollo 17 poikilitic impact melt breccias were initially interpreted to be directly related to the Serenitatis basin formation. Here we present petrological, geochemical, and U‐Pb geochronological investigations of the poikilitic impact melt of Apollo 73155,69 which was sampled from the South Massif of the Taurus‐Littrow valley. Nanoscale secondary ion mass spectrometry analyses of well‐preserved poikilitic zircons from sample 73155,69 yield a uniform 207Pb/206Pb age population with a weighted mean age of 3921 ± 14 Ma. The zircons have distinctly high concentrations of Y (3279−6347 ppm) and Th (254−302 ppm) compared with other Apollo 17 zircons. These characteristics, together with their textures, are remarkably similar to those of zircons from high‐Th melt breccias from Apollo 12 samples and lunar meteorite Sayh al Uhaymir 169 attributed to the formation of the high‐Th deposits of the Imbrium basin. We therefore propose an Imbrium provenance for melt component in 73155,69. Our results provide new evidence for components of Imbrium‐type ejecta occurring among the South Massif breccias. Consequently, the Apollo 17 poikilitic impact melt breccias may not represent Serenitatis ejecta.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.361
Teacher spread0.308 · 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 designBench or experimental
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

Citations22
Published2019
Admission routes1
Has abstractyes

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