MétaCan
Menu
Back to cohort
Record W2891678200 · doi:10.1190/segam2018-2998528.1

3D finite-volume time-domain electromagnetic modeling of graphitic faults using unstructured grids

2018· article· en· W2891678200 on OpenAlexaff
Xushan Lu, Colin G. Farquharson, Jean-Marc Miehé, Grant Harrison

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsiNano Medical (Canada)Memorial University of Newfoundland
Fundersnot available
KeywordsFinite volume methodComputer scienceVolume (thermodynamics)Computational electromagneticsElectromagnetic fieldMechanicsPhysics

Abstract

fetched live from OpenAlex

Uranium deposits in the Athabasca Basin are normally related to graphitic faults which typically behave like thin conductors. Slingram-style time-domain electromagnetic (TDEM) methods are commonly used in the exploration of the uranium deposits in the Athabasca Basin. A finite-volume time-domain (FVTD) method that is designed to model the Slingram-style electromagnetic (EM) surveys in parallel is presented. Numerical experiments show that this method can reproduce results that were previously presented in the literature. Results are also shown for a real data-set from the Athabasca Basin. Presentation Date: Thursday, October 18, 2018 Start Time: 8:30:00 AM Location: 213B (Anaheim Convention Center) Presentation Type: Oral

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations4
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicGeophysical Methods and ApplicationsFrench-language works237,207