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Record W6891723376 · doi:10.48380/wk9q-xw24

Mapping radiation-damage annealing in zircon

2022· article· en· W6891723376 on OpenAlexaff

Bibliographic record

Venuedggv-e-publications · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNuclear materials and radiation effects
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRaman spectroscopyAnnealing (glass)ZirconAmorphous solidAnalytical Chemistry (journal)Crystallization

Abstract

fetched live from OpenAlex

<p align="justify">Radiation damage accumulates in the zircon lattice due to α-disintegration of trace levels of U, Th, and their α-emitting daughters. Upon heating, the lattice damage anneals in two stages by elimination of point defects and crystallization of amorphous domains. Raman spectroscopy is the method of choice to track lattice repair over the two stages due to changes in Raman positions and bandwidths (FWHM) of different bands during annealing. In annealing experiments with controlled time and temperature conditions, the process is usually monitored by Raman measurements after each experimental run. Raman mapping of partially annealed zircon proves to be even more effective than point measurements: (1) the zoning in actinide concentrations enables the comparison of annealing in zones with different initial damage; (2) spatial effects of annealing such as the fading of zoning can be taken into account; (3) tracking changes in the Raman signal from each spot in the map enables to acquire a large amount of annealing data. <p align="justify">While earlier studies produced Raman maps of zircon annealed at high temperatures, we focused on low-temperature stage I annealing. We carried out isothermal annealing experiments on four polished Plešovice zircon grains (1.5 – 2 mm diameter), at temperatures between 300 and 610 °C, with durations between 5 minutes and 70 days, mapping out four Raman bands after each annealing run. Our results show the progressive evolution of the Raman parameters with annealing time and temperature and allow the comparison to natural samples that underwent annealing during their geological history.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.931
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.253
Teacher spread0.237 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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