Characterization of a Catastrophic Flood Sediment Layer: Geological, Geotechnical, Biological, and Geochemical Signatures
Bibliographic record
Abstract
In 1996, an important rainstorm took place in the Saguenay region, Canada, that caused severe flooding and erosion of a large amount of post-glacial sedimentary material. Consequently, about 20 million tons of sediment were deposited in the upstream part of the Saguenay Fjord, covering the recent, contaminated sediments with a 10 to 60 cm thick layer of relatively clean material. This flood layer was distinguished from the pre-flood sediments by various properties: low consistency and low resistance, high water content, the absence of benthic organisms, or the presence of inherited geochemical components. In this study, we evaluated the criteria used by the various investigators to identify the 1996 flood deposit, then finally compared its signature. Subsequently, we assessed the spatial variability of the deposit and its effect on the interpretation of temporal studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 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".