MétaCan
Menu
Back to cohort
Record W2889916649 · doi:10.1111/ter.12358

Direct observation of dislocation nucleation in pyrite using combined electron channelling contrast imaging and electron backscatter diffraction

2018· article· en· W2889916649 on OpenAlexaff
Anna Rogowitz, Stefan Zaefferer, Renelle Dubosq

Bibliographic record

VenueTerra Nova · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Ottawa
FundersAustrian Science Fund
KeywordsChannellingElectron backscatter diffractionMisorientationDislocationNucleationMaterials scienceCrystal (programming language)CrystallographyTransmission electron microscopyGrain boundaryCondensed matter physicsGeologyComposite materialMicrostructureNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Abstract Crystal‐plastic deformation is one of the main mechanisms that can accommodate large amounts of strain within the lithosphere. Despite the requirement of understanding dislocation nucleation and arrangement, the only accepted method for direct observation of dislocations in geological materials so far is transmission electron microscopy. Herein, we present a study using a combination of electron channelling contrast imaging (ECCI) and electron backscatter diffraction (EBSD) to visualize and analyse crystal defects in pyrite deforming close to the crystal plastic to brittle transition zone. Structures in focus include (a) dislocation nucleation at crack‐tips and (b) the reactivation of mode I cracks accompanied by the nucleation of dislocations and crystal‐plastic behaviour resulting in the development of complex dislocation structures and low‐angle grain boundaries. EBSD maps reveal an increase in misorientation towards micro‐cracks, consistent with a greater dislocation density along cracks observed by ECCI.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTerra NovaSame topicHigh-pressure geophysics and materialsFrench-language works237,207