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Record W2090350515 · doi:10.3189/172756506781828854

Time-lapse imaging of subglacial drainage conditions using three-dimensional inversion of borehole electrical resistivity data

2006· article· en· W2090350515 on OpenAlexfundno aff
Bernd Kulessa, Bryn Hubbard, Giles H. Brown

Bibliographic record

VenueJournal of Glaciology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsGeologyElectrical resistivity and conductivityBoreholeElectrical resistivity tomographyHydraulic conductivityGeomorphologyPorosityDrainageFluvialSoil scienceHydrology (agriculture)MineralogyGeotechnical engineeringStructural basinSoil water

Abstract

fetched live from OpenAlex

Abstract We recorded electrical resistivity data at the base of four boreholes drilled through Haut Glacier d’Arolla, Switzerland. The data were acquired repetitively every hour over two diurnal hydrological cycles in the late melt season, separated by 10 days. Constrained three-dimensional (3-D) data inversion allowed reconstruction of hourly variations in bulk resistivity in the subglacial sediment layer. Inverted resistivity models reflect the establishment of channelized subglacial drainage in the study area between the two hydrological cycles, in agreement with previous work. Daily variations in bulk and water resistivity are in phase, and bulk resistivity amplitudes decrease away from the subglacial channel. Using selected electrical–hydraulic relationships, we estimate metre-scale changes in the hydraulic conductivity and porosity of the subglacial sediment layer, accounting for increasing clay content and decreasing median grain radius with distance from the channel. Hydraulic conductivity and porosity were respectively calculated to decrease from (6.4 ± 2.1) × 10 –2 ms –1 and 0.34 ± 0.01 at the channel to (3.3 ± 2.2) × 10 –2 ms –1 and 0.26 ± 0.01 at a distance of 5m from it. The hydraulic conductivity estimates are in agreement with previously inferred values, and the porosity estimates fall within the expected range for unlithified subglacial sediments. We conclude that collection and inversion of repeat 3-D subglacial resistivity data is feasible and has the capacity to generate multidimensional images of subglacial hydraulic processes and properties.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.273
Teacher spread0.248 · 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 designObservational
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

Citations20
Published2006
Admission routes1
Has abstractyes

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