The July 1996 flood deposit in the Saguenay Fjord, Quebec, Canada: Implications for sources of spatial and temporal backscatter variations
Bibliographic record
Abstract
In July 1996 a major rainstorm and flood took place in the Saguenay Fjord. Backscatter strength measurements made with a Simrad EM1000 multibeam echosounder in 1993, 1997 and 1999 have shown spatial and temporal variations, which are interpreted in relation to the occurrence of the flood. After empirical calibration of the different maps the data show an overall diminution of 5 dB in backscatter strength in 1997, 1 yr after the flood took place, while the data sets obtained in 1993 and 1999 show comparable levels of backscatter strength. The different data sets show a similar pattern of low and high backscatter patches, which represent variations of the backscatter strength of a few decibels. Several grain size and water content measurements were also carried out on sediment box core and grab samples from the Fjord bottom in 1997 and 1999. These have shown that the areas with higher acoustic backscatter correspond to the finer sediments, while the low backscatter patches correspond to the coarser material. The data show little relation between water content and backscatter strength, thus indicating a poor dependence between the impedance terms (bulk density and sound speed) and the backscatter. Having taken this into account, the major contribution to backscatter strength is assumed to result from differences in surface and volume roughness of the sediment. Since finer grain sizes offer higher backscatter the grain size of the sediment is not considered as being a major contributor to roughness and hence, backscatter strength. The major factor that seems to control roughness generation in the Saguenay Fjord is considered to be bioturbation. The areas where geological processes most physically disturb the bottom, which coincide with the areas where also most accumulation takes place and the coarser grain sizes are deposited, are more sparsely colonized by organisms. This results in a lower degree of bioturbation, lower roughness and thus, backscatter strength. This hypothesis helps explain the variation in backscatter strength observed between the different measurement years. The several million tons of sediment deposited in the Fjord bottom after the 1996 flood buried the benthic fauna, which was still recovering 1 yr later. The less bioturbated sediment at this time would present lower roughness with respect to the 1993 and 1999 data resulting in a lower backscatter strength.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".