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Record W2327101503 · doi:10.4133/1.4721709

A Comparison of AEM Inversion Methods for Discontinuous Permafrost near Fort Yukon, Alaska

2012· article· en· W2327101503 on OpenAlex
Burke J. Minsley, Leif H. Cox, Ross Brodie, Glenn A. Wilson, Jared D. Abraham, Micheal Zhdanov

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSymposium on the Application of Geophysics to Engineering and Environmental Problems 2012 · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostArcticGeologyInversion (geology)ThermokarstClimate changePhysical geographyGeomorphologyElectrical resistivity tomographyEarth scienceGeophysicsOceanographyElectrical resistivity and conductivityGeography

Abstract

fetched live from OpenAlex

Permafrost is a predominant physical feature of Arctic and sub‐Arctic regions, and is sensitive to climate change. How warming of the permafrost affects near‐surface hydrologic processes, ecosystems, and infrastructure is not clearly understood. A better understanding of the dynamic distribution and physical properties of permafrost, from continuous to discontinuous, provides knowledge of how the permafrost may change in the future and help inform engineering and sustainable management strategies. In June 2010, the US Geological Survey acquired 875 line km of RESOLVE frequency‐domain airborne electromagnetic (AEM) data over a ∼300 sq. km block near Fort Yukon in Alaska for imaging permafrost characteristics at various scales. The AEM data have been studied with 1D and 3D inversion algorithms. In this area, the 1D approximation is generally valid, but may be violated in areas of sharp lateral resistivity contrasts where low resistivity unfrozen sediments are surrounded by high resistivity permafrost. We explored whether the resolution of weakly 3D features could be improved through the use of holistic inversion (3D model parameterization with 1D modeling) or full 3D inversion, both of which are compared with independent 1D inversions. However, in addition to differences in dimensionality, there are also differences in model parameterization and regularization between the various AEM inversion methods. We have attempted to understand how these differences are manifested in the inverted models in order to assess the features resolved by each inversion. Resistivity models produced from the different inversions compare favourably with known permafrost features, and have also suggested some previously unseen permafrost features. We have examined unfrozen areas, such as the talik interpreted beneath Twelvemile Lake that may play an important hydrogeological role. Reliable interpretations of the 3D resistivity models surrounding taliks and other thawed subsurface features are critical for assessing whether or not these features are fully connected through the permafrost.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.386

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)0.0000.000

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 head0.020
GPT teacher head0.261
Teacher spread0.240 · 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