Grand Banks Scour Catalogue (GBSC) GeoDatabase
Bibliographic record
Abstract
In the late 1990's and early 2000's, NRCan, through the Geological Survey of Canada (GSC), conducted research on the distribution and severity of seabed iceberg scour on the Grand Banks. One of the key products of that work was a research database that recorded the location and geometric parameters for all mapped seabed scours on the Grand Banks. The Grand Banks Scour Database (GBSC) was developed under GSC contract to Canadian Seabed Research Ltd. (CSR) and updated sporadically when funding allowed new data to be captured. With the wind-down of GSC work on Grand Bank seabed scour, it is important to formalize the database and release a standardized database in a documented and publicly accessible format. This report documents the development of a simplified GIS Geodatabase that represents the key scour parameters. The scours recorded in the GBSC were identified and measured from various geophysical data sets including; sidescan sonar, multibeam sonar, sub-bottom profiler, single beam echo sounder, and high resolution single channel seismic (Huntec) systems. The GBSC survey coverage consists of an irregular network of regional lines (22,704 km) and site surveys (4762 km2) conducted by the GSCA and the petroleum industry. The simplified GBSC Geodatabase compiled during this study contains 5366 iceberg furrow features and 2680 iceberg pit features. The interaction of ice and seafloor sediments may result in a variety of ice scour types and shapes. Features stored in the GBSC include furrows, furrows with an associated pit (s), individual pits and Pit Chains. Iceberg furrows and pits have been recorded in water depths ranging from 49 to 350 m and within sediment types of Predominantly Sand, Sand & Gravel, and Gravel. Although a significant number of furrows occur within each 10° orientation bin the general orientation mode of the GBSC furrow population is northeast - southwest. Furrow length ranges from 5 m to 10,216 m, with a mean length of 584.7 m while Pit area ranges from 84 m² to 111,300 m², with a mean area of 6193 m². Furrow width measurements range from 1 to 208 m with a mean width of 26 m. Furrow depth ranges from 0.1 m to 7.0 m, with a mean depth of 0.88 m while Pit depth ranges from 0.1 m to 8.3 m, with a mean of 1.92 m.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.026 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.043 |
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".