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Record W4391281253 · doi:10.1111/maps.14140

A sample preparation guide for clay‐rich carbonaceous chondrites

2024· article· en· W4391281253 on OpenAlex
Bennett J. K. Wilson, V. E. Di Cecco, L. A. J. Garvie, K. T. Tait, M. G. Daly

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMeteoritics and Planetary Science · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsRoyal Ontario MuseumUniversity of TorontoYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsChondriteGeologySample (material)GeochemistryAstrobiologyMineralogyChemistryMeteoriteChromatographyPhysics

Abstract

fetched live from OpenAlex

Abstract The matrix of the C2‐ungrouped Tarda meteorite contains abundant smectite minerals that swell and crumble when exposed to polar liquids, causing the sample to rapidly slake. This phenomenon presents a serious challenge when polishing the meteorite, as common polishing liquids used on carbonaceous chondrites, such as water, ethanol, ethylene glycol, and isopropyl alcohol, are polar and will cause the sample to swell, making it unsuitable for some analyses. Hexane and mineral oil are nonpolar liquids that were found to not induce swelling on highly expansive montmorillonite‐clay analog material and were effectively integrated into a polishing procedure for Tarda. Here, we detail a procedure for mounting, cutting, and polishing the Tarda meteorite to prepare a surface that is suitable for a variety of sensitive techniques, such as electron microprobe analysis. This work offers a practical methodology for the preparation of other clay‐rich samples, which may include the recently returned Ryugu and Bennu materials.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.010
GPT teacher head0.264
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