The Distribution of Ribbed Moraines in the Lac Naococane Region, Central Quebec, Canada
Bibliographic record
Abstract
Ribbed moraines are large subglacially formed transverse ridges that coverextensive areas of the beds of the former Laurentide, Fennoscandian and Irish ice sheets.Since the flow speeds and stability of ice sheets are known to be sensitive to conditionsoperating at the bed, a full understanding of the processes of ribbed moraine genesis arecritical if we are to appreciate their role in ice sheet dynamics. To date, advances inknowledge on how ribbed moraines are formed rely on inferences drawn from theircharacteristics. However, this approach is problematic given that ribbed morainecharacteristics are poorly known. Scrutiny of the literature reveals that detailedobservations are limited to small areas and rely on small sample sizes. Thus,generalisations drawn from this base cannot be regarded as being representative andremain an inadequate data source for testing the various hypotheses. The map formspart of a large study that investigated ribbed moraine characteristics in Ireland, Canadaand Sweden over a combined area of 81,000 km2 that has addressed this deficit. It showsthe distribution of ribbed moraine ridges in the Lac Naococane region, central Qu´ebecand covers an area of 32,400 km2. It comprises over 12,800 individual ridges and formspart of a database of over 33,000 individually mapped landforms which reveal ribbedmoraine characteristics to be more complex than has hitherto been reported.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".