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Record W2057423632 · doi:10.3189/002214310791968485

Seismic wave attenuation in the uppermost glacier ice of Storglaciären, Sweden

2010· article· en· W2057423632 on OpenAlexfundno aff
A. Gusmeroli, Roger A. Clark, Tavi Murray, Adam Booth, Bernd Kulessa, Brian Barrett

Bibliographic record

VenueJournal of Glaciology · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersQueen's UniversitySwansea UniversityLeverhulme Trust
KeywordsAttenuationGeologyGlacierRefractionGeodesyOffset (computer science)SeismologyPolarGeomorphologyOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract We conducted seismic refraction surveys in the upper ablation area of Storglaciären, a small valley glacier located in Swedish Lapland. We estimated seismic-wave attenuation using the spectral-ratio method on the energy travelling in the uppermost ice with an average temperature of approximately −1 °C. Attenuation values were derived between 100 and 300 Hz using the P-wave quality factor, Q P , the inverse of the internal friction. By assuming constant attenuation along the seismic line we obtained mean Q P = 6 ± 1. We also observed that Q P varies from 8 ± 1 to 5 ± 1 from the near-offset to the far-offset region of the line, respectively. Since the wave propagates deeper at far offsets, this variation is interpreted by considering the temperature profile of the study area; far-offset arrivals sampled warmer and thus more-attenuative ice. Our estimates are considerably lower than those reported for field studies in polar ice (∼500–1700 at −28°C and 50–160 at −10°C) and, hence, are supportive of laboratory experiments that show attenuation increases with rising ice temperature. Our results provide new in situ estimates of Q P for glacier ice and demonstrate a valuable method for future investigations in both alpine and polar ice.

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 score0.016
Threshold uncertainty score0.594

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)0.0010.000

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 head0.028
GPT teacher head0.247
Teacher spread0.219 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

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