Conditions for Growth and Retreat of the Laurentide Ice Sheet
Bibliographic record
Abstract
Results of three dimensional numerical modelling of the North American ice sheets in response to the Earth's orbital radiation variations are reviewed in relation to the conditions for formation and retreat of the ice sheets. The last interglacial develops as a clear result of the preceding high summer radiation levels and is not very dependent on the climatic paramaterisation. The magnitude and timing of the last glacial maximum provides a means of fine tuning the climatic parameterisation. In between these two periods the extent of ice sheet advances and retreat is strongly sensitive to the magnitude of the ice sheet albedo feedback parameter. The time changes of the radiation, climate, ice sheet cover and bedrock depression are out of phase and as a result equilibrium is not attained. The distribution of land surface elevation plays a key role in the pattern of seeding of the ice sheet growth and the subsequent advances, coalescence and retreat. The dispersal pattern of bedrock in till can be expected to reflect the growth and advance phases of the ice sheet development rather than the maximum configuration. Finally, the cycles of ice ages over the last 500,000 years from the modelling follows the occurrence of extreme summer radiation levels over a wide latitude band of 40-80°N due to coincidence of obliquity and perihelion features superimposed on the hysteresis effects of the ice cover.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".