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Record W2324869791 · doi:10.3997/2214-4609-pdb.191.p6

Time-Domain Electromagnetic Resistivity Mapping Of A Fjord-Head Delta

2002· article· en· W2324869791 on OpenAlexaffabout
Melvyn E. Best, Jeff E. Gutsell, John J. Clague

Bibliographic record

Venue15th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGeologyFjordDeltaGeomorphologyElectrical resistivity and conductivitySiltBedrockSedimentHydrology (agriculture)MineralogyGeotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

An electromagnetic (EM) survey was conducted on the Zeballos River delta located approximately<br>300 kilometres north of Victoria, British Columbia, Canada to determine whether EM methods can help<br>delineate the three-dimensional architecture of a fjord-head delta. The EM data were collected using a<br>Geonics EM-47 system with a 40 m transmitter loop. The data were downloaded and subsequently edited<br>and interpreted using the TEMIXGL layered earth inversion package from Interpex. The interpretation<br>provided a regional picture of the three dimensional resistivity structure of the delta. Throughout most of<br>the region surveyed, a relatively thick layer of resistive (> 400 ohm-m) sediment (gravel and sand - delta<br>topsets and foresets) overlies more conductive (10 - 20 ohm-m) sediment (silt and clay - delta bottomsets)<br>which in turn overlies resistive (> 2000 ohm-m) bedrock. Within the intertidal zone, the shallow sediments<br>were saturated with sea water and hence very conductive. However, we were able to determine the depth<br>to more resistive (fresh water) gravel and sand and, in some areas, resistive bedrock. The results of this study<br>indicate that EM resistivity surveying can provide constraints on sediment type and thickness which, when<br>used in conjunction with geological mapping, help improve our understanding of the three-dimensional<br>architecture of these deltas.

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: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.500

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 head0.008
GPT teacher head0.173
Teacher spread0.165 · 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

Citations0
Published2002
Admission routes2
Has abstractyes

Explore more

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