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Record W4386897477 · doi:10.5194/gchron-2023-15-ac3

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2023· peer-review· en· W4386897477 on OpenAlexaff
Donald W. Davis

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsUniversity of Toronto
FundersLunds Universitet
KeywordsRecoilRedistribution (election)PhysicsNuclideAtomic physicsChemistryAnalytical Chemistry (journal)CrystallographyNuclear physics

Abstract

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Abstract. Atom probe tomography of 238U and 206Pb has been applied to baddeleyite crystals from the Hart Dolerite (1791 ± 1 Ma) and the Great Dyke of Mauritania (2732 ± 2 Ma) in an effort to constrain the average nuclear recoil distance of U-series daughter nuclei and thereby correct U-Pb ages determined on small baddeleyite crystals for alpha-recoil loss of Pb. Both crystals were thought to expose natural crystal surfaces providing a boundary where maximum recoil loss could be observed, but both surfaces showed no adjacent variations in Pb concentrations. However, the Great Dyke sample shows U zoning and the associated 206Pb zoning is affected by alpha recoil. A forward modelling approach was used where 206Pb redistribution functions were determined for a range of possible alpha recoil distances and synthetic 206Pb/238U profiles were determined from the convolution of the observed U profile with the redistribution functions. These can be compared to the observed 206Pb/238U profile. A complication is that the 400 nm range of sampling is lower than the range of possible alpha recoil redistribution effects. In order to get a realistic match to the observed 206Pb/238U profile, it was necessary to extrapolate the observed zoning as an oscillatory pattern. This gives a best estimate for the average alpha recoil distance of about 40 nm.

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)0.003
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.117
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0330.029
Insufficient payload (model declined to judge)0.1170.096

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 head0.029
GPT teacher head0.298
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2023
Admission routes1
Has abstractyes

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