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Record W2342629655 · doi:10.1021/acs.analchem.6b00373

STEM EDX Nitrogen Mapping of Nanoinclusions in Milky Diamonds from Juina, Brazil, Using a Windowless Silicon Drift Detector System

2016· article· en· W2342629655 on OpenAlexaff
J. Rudloff-Grund, Frank E. Brenker, Katharina Marquardt, Felix V. Kaminsky, Anja Schreiber

Bibliographic record

VenueAnalytical Chemistry · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsStornoway Diamond (Canada)
FundersDeutsche Forschungsgemeinschaft
KeywordsSiliconSilicon drift detectorDetectorScanning transmission electron microscopyChemistrySpectroscopyAnalytical Chemistry (journal)Milky WayTransmission electron microscopyNanotechnologyMineralogyOpticsMaterials sciencePhysicsEnvironmental chemistry

Abstract

fetched live from OpenAlex

Energy-dispersive X-ray spectroscopy (EDX) performed using scanning transmission electron microscopy (STEM) in combination with a windowless detector setup allows high-resolution imaging and chemical composition mapping even of light elements present in low concentrations. The used TEM-system combines a field emission electron source with four silicon drift detectors allowing for high detection sensitivity. We used this enhanced system to investigate 20 to 200 nm sized inclusions in milky diamonds from Rio Soriso, Juina area, Brazil. The diamonds act as a chemical inert container and therefore protect their inclusions from further chemical reactions with their surroundings. We visualize the presence and distribution of nitrogen within focused ion beam (FIB) slices containing these nanoinclusions. The investigation of these specific diamonds may open a new window to deeper parts of the Earth (>660 km) as they represent pristine material of this deep mantle environment.

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 score0.006
Threshold uncertainty score0.012

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 head0.014
GPT teacher head0.218
Teacher spread0.203 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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