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Record W4402152914 · doi:10.5194/tc-18-3699-2024

Misidentified subglacial lake beneath the Devon Ice Cap, Canadian Arctic: a new interpretation from seismic and electromagnetic data

2024· article· en· W4402152914 on OpenAlexafffundabout
Siobhan Killingbeck, A. Rutishauser, Martyn Unsworth, Ashley Dubnick, Alison S. Criscitiello, James Killingbeck, Christine F. Dow, Tim Hill, Adam Booth, Brittany Main, Éric Brossier

Bibliographic record

Venue˜The œcryosphere · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of OttawaYukon UniversitySimon Fraser UniversityUniversity of AlbertaUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaWeston Family Foundation
KeywordsGeologyRadarGround-penetrating radarArcticGlaciologyInversion (geology)GeomorphologySea ice thicknessGeophysicsAttenuationSeismologyOceanographyArctic ice packMagmatismTectonics

Abstract

fetched live from OpenAlex

Abstract. In 2018 the first subglacial lake in the Canadian Arctic was proposed to exist beneath the Devon Ice Cap, based on the analysis of airborne radar data. Here, we report a new interpretation of the subglacial material beneath the Devon Ice Cap, supported by data acquired from multiple surface-based geophysical methods in 2022. The geophysical data recorded included 9 km of active-source seismic-reflection profiles, seven transient electromagnetic (TEM) soundings, and 17 magnetotellurics (MT) stations. These surface-based geophysical datasets were collected above the inferred locations of the subglacial lakes and show no evidence for the presence of subglacial water. The acoustic impedance of the subglacial material, estimated from the seismic data, is 9.49 ± 1.92 × 106 kg m−2 s−1, comparable to consolidated or frozen sediment. The resistivity models obtained by inversion of both the TEM and MT measurements show the presence of highly resistive rock layers (1000–100 000 Ω m) directly beneath the ice. Re-evaluation of the airborne reflectivity data shows that the radar attenuation rates were likely overestimated, leading to an overestimation of the basal reflectivity in the original radar studies. Here, we derive new radar attenuation rates using the temperature- and chemistry-dependent Arrhenius equation, and when applied to correct the returned bed power, the bed power does not meet the basal reflectivity threshold expected over subglacial water. Thus, the radar interpretation is now consistent with the seismic and electromagnetic observations of dry or frozen, non-conductive basal material.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.997

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.217
Teacher spread0.198 · 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.

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

Citations9
Published2024
Admission routes3
Has abstractyes

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