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Record W2022176197 · doi:10.1149/1.3570080

Comparison between FIB-SEM Experimental 3-D Reconstructions of SOFC Electrodes and Random Particle-Based Numerical Models

2011· article· en· W2022176197 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

VenueECS Transactions · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsMaterials scienceFocused ion beamPorosityVolume fractionElectrodeParticle (ecology)Scanning electron microscopeSolid oxide fuel cellIonComposite materialPhysics

Abstract

fetched live from OpenAlex

There has been a rapidly growing interest in three-dimensional micro-structural reconstruction of solid oxide fuel cell (SOFC) electrodes so as to derive more accurate descriptors of the pertinent geometric and effective transport properties. Experimental based reconstruction technique is based on processing of a sequence of images obtained by dual-beam focused ion beam-scanning electron microscopy. Numerical reconstruction of electrodes is based on random distribution of particles with specified nominal phase volume fractions (porosity and electron-conducting particle volume fraction). In this study, we compare both approaches and investigate ways of improving model geometries so that they match better with experimental measurements.

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)0.000
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 score0.357
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.046
GPT teacher head0.304
Teacher spread0.258 · 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