Thin-layer effects in glaciological seismic amplitude-versus-angle (AVA) analysis: implications for characterising a subglacial till unit, Russell Glacier, West Greenland
Bibliographic record
Abstract
Abstract. Seismic amplitude-versus-angle (AVA) methods are a powerful means of quantifying the physical properties of subglacial material, but serious interpretative errors can arise when AVA is measured over a thinly-layered substrate. A substrate layer with a thickness less than 1/4 of the seismic wavelength, λ, is considered "thin", and reflections from its bounding interfaces superpose and appear in seismic data as a single reflection event. AVA interpretation of subglacial till can be vulnerable to such thin-layer effects, since a lodged (non-deforming) till can be overlain by a thin (metre-scale) cap of dilatant (deforming) till. We assess the potential for misinterpretation by simulating seismic data for a stratified subglacial till unit, with an upper dilatant layer between 0.1–5.0 m thick (λ / 120 to > λ / 4, with λ = 12 m). For dilatant layers less than λ / 6 thick, conventional AVA analysis yields acoustic impedance and Poisson's ratio that indicate contradictory water saturation. A thin-layer interpretation strategy is proposed, that accurately characterises the model properties of the till unit. The method is applied to example seismic AVA data from Russell Glacier, West Greenland, in which characteristics of thin-layer responses are evident. A subglacial till deposit is interpreted, having lodged till (acoustic impedance = 4.26±0.59 × 106 kg m−2 s−1) underlying a water-saturated dilatant till layer (thickness < 2 m, Poisson's ratio ~ 0.5). Since thin-layer considerations offer a greater degree of complexity in an AVA interpretation, and potentially avoid misinterpretations, they are a valuable aspect of quantitative seismic analysis, particularly for characterising till units.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 teacher head, 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".