The Effects of the Laurentide Ice Sheet on North American Climate during the Last Glacial Maximum
Bibliographic record
Abstract
A climate model, consisting of an atmospheric general circulation model coupled with a simple model of the oceanic mixed layer, is used to investigate the effects of the continental ice distribution of the last glacial maximum (LGM) on North American climate. This model has previously been used to simulate the LGM climate, producing temperature changes reasonably in agreement with paleoclimatic data. The LGM distribution of continental ice according to the maximum reconstruction of HUGHES et al. (1981) is used as input to the model. In response to the incorporation of the expanded continental ice of the LGM, the model produces major changes in the climate of North America. The ice sheet exerts an orographic effect on the tropospheric flow, resulting in a splitting of the midlatitude westerlies in all seasons but summer. Winter temperatures are greatly reduced over a wide region south of the Laurentide ice sheet, although summer cooling is less extensive. An area of reduced soil moisture develops in the interior of North America just south of the ice margin. At the same time, precipitation increases in a belt extending from the extreme southeastern portion of the ice sheet eastward into the North Atlantic. Some of these findings are similar to paleoclimatic inferences based on geological evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".