Reorganization of ice sheet flow patterns in Arctic Canada and the mid‐Pleistocene transition
Bibliographic record
Abstract
Evidence for the evolution of Laurentide Ice Sheet (LIS) basal thermal regime patterns during successive glaciations is poorly preserved in the geologic record. Here we explore a new approach to constrain the distribution of cold‐based ice across central Baffin Island in the eastern Canadian Arctic over many glacial‐interglacial cycles by combining till geochemistry and cosmogenic radionuclide (CRN) data. Parts of the landscaped with geomorphic evidence for limited glacial erosion are covered by till characterized by high chemical index of alteration (CIA) values and CRN concentrations requiring complicated burial‐exposure histories. Till from regions scoured by glacial erosion have CIA values indistinguishable from local bedrock and CRN concentrations that can be explained by simple exposure following deglaciation. CRN modeling results based on these constraints suggest that the weathered tills were deposited by 1.9 to 1.2 Ma, and by that time the fiorded Baffin Island coastline must have developed close to its modern configuration as piracy of ice flow by the most efficient fiord systems resulted in a major shift in the basal thermal regime across the northeastern LIS. The resultant concentration of ice flow in fewer outlet systems may help explain the cause of the mid‐Pleistocene transition from 41‐ to 100‐kyr glacial cycles.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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 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".