Imaging Active Turbidity Currents on a Fjord Delta
Bibliographic record
Abstract
Using repetitive multibeam surveys at time scales ranging from annual to daily and even hourly, the temporal evolution of active channels on the front of a fjord delta in British Columbia has been monitored. During the peak summer discharge period, rapidly migrating bedforms on the delta top channel document the flux of sediment into the fjord. The lip of the delta is seen to progressive advance over a period of several days interspersed with abrupt regression during discrete mass wasting events. Those events are clearly strongly correlated with the low water spring tides when the off-delta currents are highest and the hydrostatic pressure at the seabed is lowest. During those events, bedforms in the channel abruptly migrate upslope. Most recently, imaging multibeam sonars have been suspended from a moored vessel directly above the active channels. Using this geometry, the passage of the head, body and wake of multiple turbidity current flows can be observed with a half second update rate. Massive release of gas as a result of the head passage is clearly documented. Together with current velocity and suspended sediment measurements from co-located ADCP’s and optical backscatter probes, insights into the flow dynamics of the turbidity currents are inferred. Presenter Bio John Hughes Clarke has degrees in Geology and Oceanography from Oxford, Southampton and Dalhousie. His primary fascination is with marine sediment transport, particularly in deep water. His original exposure to swath sonar systems was in 1984 looking at the record of the 1929 turbidity current. Since that time he has increasingly focused on the information content available from those systems. He has spent the last 23 years as part of, and now leading, the Ocean Mapping Group at the University of New Brunswick in Canada.
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 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".