Controls upon the location and size of glacial overdeepenings: PhD thesis
Bibliographic record
Abstract
Overdeepening is an important glaciological and geomorphological process that has the potential to influence the response of ice masses to climatic changes. We have examined several hundred glacial overdeepenings proximal to/ within Labrador, Canada, to investigate the controls upon overdeepening location and size. Our analyses show that overdeepening appears to correlate strongly with glacial confluence and, importantly, the correlation is strongest where confluence-geometry indicates the speed up of ice-flow. Further, we find that the magnitude of ice-flow speed up correlates with overdeepening depth only for confluences situated in or near major geological fault-zones. Our findings therefore support the hypothesis that overdeepening can be initiated by an increase in ice velocity. Further, we conclude that overdeepening is most efficacious where fractured bedrock enables efficient quarrying.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".