Geophysical investigation of coastal roads vulnerable to erosion, Bay Bulls, \nNewfoundland and Labrador
Bibliographic record
Abstract
In the town of Bay Bulls, on the east-facing coast of the Avalon Peninsula, Newfoundland, \ncoastal roads run close to the steep, rocky shoreline on both sides of a deep bay. Three sections of \nroad, each about 100 m in length, have been identified as vulnerable to erosional processes. To \nimage the surface and subsurface structure in these three areas, two geophysical methods: ground \npenetrating radar (GPR), direct current resistivity/induced polarization (DCR/IP), and real-time \nkinetics global positioning system (RTK) were used. The primary aims of this study were to \ncharacterize the subsurface in these three vulnerable areas and to test the utility of the geophysical \nmethods in identifying structural weaknesses. \n On the north side of the bay, at “Bread and Cheese”, the road dips down over a culverted \ncreek in a highly fractured area. At “the Cliff”, the road has been widened bay-ward with the use \nof a wooden retaining wall. “The Quays” is on the south side of the bay, where a narrow inlet with \nsteep cliffs comes very close to the road. At all three sites, RTK data revealed locations where the \nroad surface sloped bay-ward, suggesting undesirable creepage in the roadbed. Also, at all three \nsites, DCR data from deeper levels showed broad (10s of m) variations in the steeply dipping strata \nof the bedrock, possibly related to their ease of erosion. At Bread and Cheese, GPR showed depth \nto bedrock and the horizontal extent of the weaker, fractured region, while DCR measurements \nsuggest the most fractured location is to the west of the culvert. At the Cliff, GPR profiles and 3D \nimaging identified the locations and lengths of wooden beams extending from the retaining wall \nunder the widened road. At the eastern parts of the Quays, GPR identified shallow bedrock \nfollowing the along-road topography of the road. To the west, the road appears to cover sediments. \nAnalysis of the geophysical data and geological information indicates that the hard bedrock \nand the shape and orientation of the bay mean that wave action is not a major factor affecting the \nstability of coastal roads and that the overland flow of water and groundwater is more of a concern \nat the three vulnerable sites.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".