MétaCan
Menu
Back to cohort
Record W2091137495 · doi:10.1002/sca.20052

Skirting: A Limitation for the Performance of X‐ray Microanalysis in the Variable Pressure or Environmental Scanning Electron Microscope

2007· article· en· W2091137495 on OpenAlex

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

VenueScanning · 2007
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scanning electron microscopeScanning electron microscopeMicroanalysisMicroscopeAnalytical Chemistry (journal)X-rayMaterials scienceOpticsChemistryComposite materialPhysicsChromatography

Abstract

fetched live from OpenAlex

The variable pressure or environmental scanning electron microscope (VP-SEM; ESEM) has become the microscope of choice for many scientists and technologists. Hence, the development of robust methods for X-ray microanalysis, limited by skirting, has become critical. In this paper, two pressure variation correction methods (Doehne and Gauvin) are compared. Both of these methods appear to be effective; the results were found to be well within 10% of the values obtained at 0 Pa. The Doehne method is dependent on an empirical factor (D), therefore the accuracy of the results will depend on the accuracy of this value. Also the Doehne method is compromised by the nonlinearity of the response with pressure. The Gauvin method is more user-friendly and more precise when considering the total range of pressure.

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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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