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Record W4408466442 · doi:10.5194/egusphere-egu25-16461

Using the ‘War Sands’ of World War II as Tracers of Geomorphic Processes and Rates – Sedimentology on the 80th Anniversary of the Allied Invasion of Normandy, France

2025· preprint· en· W4408466442 on OpenAlexaff
Samuel M. Hudson, Dallin Laycock, Erin A. L. Pemberton, Glen Burridge, Cassidy Grover, Kassandra Ramirez, Olivia Tatum, J.R. Robinson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsSedimentologyGeologyGeochemistryChemistry

Abstract

fetched live from OpenAlex

Sediment accumulation rates can be notoriously hard to measure over geomorphic timescales in coastal systems. Anthropogenic metals, if their provenance can be constrained, can act as tracers and help to build a much more detailed understanding of these processes on decadal/century timescales. Past industrial activity and the history of warfare along the coast of Normandy, France has been the subject of intense study due to its significance to historians, having been the site of the largest naval invasion in history during World War II. Previous publications attribute much of the anthropogenic metal on these beaches to the battle and related events, and this detailed sedimentological study across the five main landing sites shows consistent presence of anthropogenic metal based on approximately 300 samples collected from 16 surface transects and 21 sediment cores. Along with characterization of metals, sediment size distribution was quantified for each of the samples.Sediment size varies significantly across all five sampled beaches, ranging from very fine to very coarse sand and pebbles. Grain size distribution shows consistent trends however, with all surface transects showing an abrupt decrease in grain size at the transition from the backshore to the foreshore. For all but one locality (Sword Beach, which is near the mouth of the Orne River and has a higher average grain size), surface samples taken below the high tide mark are dominated by fine to very fine sands (greater than 80%). Sample grain size distribution changes very little within the active foreshore, showing a higher degree of sorting and textural maturity when compared with coarser and more poorly sorted samples from above the high tide line. This clear break in mean sediment size and sorting is mimicked by distribution of anthropogenic metals, with a pronounced increase in concentration of these metals below the high tide mark, where system energy is greatest.While the high tide line (foreshore/backshore transition) marks a pronounced shift in both grain size and metal concentration based on surface samples, abrupt transitions in grain size and metals concentration do not align in the same way at depth. Samples show a clear and abrupt increase in grain size at ~15 cm for all but Sword Beach (~45 cm), but there is little to no obvious change in metals concentration at this level. Rather, there is an abrupt decrease in metals concentration deeper, at ~45 cm depth. This decoupling of grain size and metals concentration suggests that metal concentration in the cores is potentially a function of time rather than depositional energy and processes. If much of this material is attributed to the invasion of Normandy in 1944, this suggests an approximate sediment accumulation rate of ~ 0.57cm/year. If metals can be partially attributed to earlier industrial activity, such as the opening of the Société Métallurgique de Normandie in 1912, net annual sediment gain is slightly lower. Ongoing work promises to better constrain sedimentary processes along the Normandy coast and other analogous coastlines both in the present and ancient geologic records.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.304
Teacher spread0.220 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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