Palaeogeographical reconstruction and hydrology of glacial Lake Purcell during <scp>MIS</scp> 2 and its potential impact on the Channeled Scabland, <scp>USA</scp>
Bibliographic record
Abstract
Large, ice‐marginal lakes that were impounded by the maximally extended Cordilleran Ice Sheet (CIS) provided source waters for the extraordinarily large floods that formed the Channeled Scabland of Washington and Idaho, USA. However, flood flows that drained CIS meltwater and contributed to landscape evolution during later stages of deglaciation have hitherto been poorly investigated. This paper provides the first evidence for such a late deglacial floodwater source: glacial Lake Purcell (gLP). Sedimentary evidence records the northward extension of gLP from Idaho, USA into British Columbia, Canada and establishes its minimum palaeogeographical extent. Sedimentary evidence suggests that the deglacial Purcell Lobe was a capable ice dam that impounded large volumes of gLP water. A review of glacio‐isostatically affected lakes during CIS deglaciation suggests that gLP could have been subjected to tilts ranging from 0 to >1.25 m km−1. Sedimentary evidence suggests high lake plane tilts (⪆1.25 m km−1) are the most likely to have affected gLP. Using this, the palaeogeography and volume of gLP are modelled, revealing that ~116 km3 of water was susceptible to sudden drainage into the Channeled Scabland via the Columbia River system. This calculation is supported by sedimentary and geomorphic evidence compatible with energetic flood flows along the gLP drainage route and suggests gLP drained suddenly, causing significant landscape change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".