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Record W4239884404 · doi:10.22215/etd/2016-11611

Geophysical Applications of Electrical Impedance Tomography

2016· dissertation· en· W4239884404 on OpenAlexaff
Alistair Boyle

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsCarleton University
Fundersnot available
KeywordsElectrical impedance tomographyElectrical resistivity tomographyComputer scienceTomographyGeophysicsCorrectnessElectrical impedanceGeologyLandslideRemote sensingElectrical resistivity and conductivityEngineeringGeotechnical engineeringElectrical engineeringAlgorithmPhysics

Abstract

fetched live from OpenAlex

Impedance imaging is a technique where stimulus currents are applied through electrodes to a body or the ground and measurements of the potential at other electrodes are collected. The data, along with any available prior information, are used to reconstruct an image of the conductivity distribution throughout the interior which provides diagnostic, cost effective information upon which decisions can be based for a broad array of geophysics, biomedical and industrial applications. The same technique is known as (biomedical) Electrical Impedance Tomography (EIT) and (geophysics) Electrical Resistivity Tomography (ERT). New geophysical applications have arisen for the automated monitoring of slope stability risks for natural landslides, transport embankments and cuttings, mine tailings dams and piles, and remote infrastructure in changing climatic environments. When impedance imaging Thank you to the many people who made this work such a rewarding experience

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.002
GPT teacher head0.205
Teacher spread0.202 · 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.

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

Citations12
Published2016
Admission routes1
Has abstractyes

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