The role of structural heterogeneity in glacier ice deformation: Insights from Planpincieux Glacier
Bibliographic record
Abstract
Abstract. Natural glacier ice is not a monophasic, isotropic material as commonly assumed in models based on Glen-Nye's flow law. It can contain crevasses, develop crystallographic preferred orientations, and include mixtures of debris and interstitial water in temperate glaciers. Understanding the influence of such structural heterogeneities on deformation is therefore essential for accurately modeling glacier dynamics. In this study, we investigate the multi-scale evolution of structural heterogeneities with depth in the Planpincieux Glacier (Italian Mont Blanc massif) and evaluate their respective influence on ice deformation using a borehole instrumented with an optical televiewer, a full-waveform sonic logger, a piezometer, and an inclinometer chain. Complementary GNSS and seismic data provide additional constraints on hydrological activity and surface motion. Optical and sonic logging reveal two main families of heterogeneities: open and closed crevasses in the upper 60 m, and debris-rich layers near the bedrock interface. Acoustic data show continuous but opposite trends in both P- and Stoneley-wave velocities with depth, interpreted as reflecting an increase in water content but a decrease in permeability. Tiltmeter measurements indicate that roughly one-third of the surface velocity is accommodated by internal deformation, with pronounced strain localization near the bedrock, particularly within debris-rich layers. These layers exhibit enhanced strain following hydrological drainage events, suggesting a coupling between mechanical heterogeneity, basal hydrology, and strain localization. The results highlight that glacier friction laws may be significantly influenced by such heterogeneities, including the effects of interstitial water and debris on local mechanical behavior.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".