Pattern and chronology of glacial <scp>L</scp>ake <scp>P</scp>eace shorelines and implications for isostacy and ice‐sheet configuration in northeastern <scp>B</scp>ritish <scp>C</scp>olumbia, <scp>C</scp>anada
Bibliographic record
Abstract
Recognition of positions of glacial lakes along the margin of continental ice sheets is critical in reconstructing ice configuration during deglaciation. Advances in remote sensing technology (e.g. LiDAR ) have enabled the generation of accurate digital‐elevation models ( DEMs ) that reveal unprecedented geomorphic detail. Combined with geographical information systems, these tools have considerably advanced the mapping and correlation of geomorphic features such as relict shorelines. Shorelines of glacial L ake P eace ( GLP ) developed between the L aurentide and C ordilleran ice sheets in northeastern B ritish C olumbia and northwestern A lberta. Shoreline mapping from high resolution DEMs produced more than 55 500 elevation data points from 3231 shorelines, enabling the identification of four major phases of GLP : Phase I (altitude 960–990 m a.s.l.); Phase II (890–915 m a.s.l.); Phase III (810–865 m a.s.l.); and Phase IV (724–733 m a.s.l.). The timing of Phase II of GLP is estimated by two optical ages of <16.0±2.5 and 14.2±0.5 ka BP . Extensive mapping of the shorelines allows for measuring of glacial isostatic adjustment as ice retreated. Shorelines currently dip to the northeast at around 0.4–0.5 m km −1 . This slope reflects the asynchronous retreat of the C ordilleran ( CIS ) and L aurentide ( LIS ) ice sheets. The relative uplift in the southwest of the study area within the R ocky M ountains and foothills suggests that the Late Wisconsinan ( MIS 2) CIS persisted in the foothill after the LIS lost mass and retreated, or that the Late Wisconsinan CIS was very thick and caused deep crustal loading, which resulted in more uplift in the southwest before reaching equilibrium during, or shortly after deglaciation.
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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 | 0.003 | 0.003 |
| 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) | 0.002 | 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".