A tale of two ponds, Newfoundland, Canada
Bibliographic record
Abstract
Bathymetric surveys of two small lakes in Newfoundland, located in different environments and separated by hundreds of kilometres, were carried out using two different survey methods—ground penetrating radar (GPR) and sound navigation and ranging (sonar). The different structures of these two disparate ponds were found to be related to the differing geology and degrees of anthropogenic influence at the two locations. In addition, the study outlined the strengths and limitations of the two survey methods. Tipping’s Pond, on the outskirts of the town of Corner Brook in western Newfoundland, is a sinkhole in a popular recreation area. It is roughly square with an area of 1.6 km2 and is slightly salty, making it largely impenetrable by radar. Bathymetric surveys with a salinity-impervious fish-finder sonar system revealed Tipping’s Pond to be bowl-shaped and more than 25 m deep in the centre. Grassy Pond, 3 km inland from the Trans-Canada Highway in eastern Newfoundland, is within an undeveloped area accessible by snowmobile in the winter. It has an irregular, elongated shape 1.2 km2 in area and is very fresh. As well as determining the bathymetry, GPR was able to determine the depth of a soft sediment layer overlying till, and to image structures within the soft sediments. The top of the sediment layer is undulating and shallow (<2.9 m deep) whereas the base of the sediments overlies sub-basins about 8 m deep.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".