Bibliographic record
Abstract
Introduction Astronauts who first orbited the Earth in the Space Shuttle described the Antarctic Ice Sheet as the most spectacular of the world's landscapes seen from space. The sight of the white snow surface, the surrounding Southern Ocean, and the sheer extent of the ice covering a continent one and a half times the size of the USA was dramatic and humbling (Fig. 14.1; Plate 45). The global scene would have been all the more dramatic about 20 ka BP at the height of the last ice age. An orbiting observer at the time would have seen the Laurentide Ice Sheet, an equally large ice mass located over Canada and the northern USA, a Greenland Ice Sheet more expanded than that of today, and a large ice sheet in northwest Europe extending from southern Britain across Scandinavia to Svalbard and northern Russia. At such a time global sea level was 120m lower than it is today and the world's climatic and vegetation zones were compressed towards the equator (Plate 1). The contrast between the two scenes is powerful testament to the scale of the environmental changes that occur in response to natural cycles of insolation received by the Earth. Ice sheets play a fundamental role in modulating global climate. The last few ice age cycles have lasted about 100 ka and display a sawtooth pattern with a long and irregular period of cooling as the ice sheets grow to their maximum, followed by an abrupt warming and a return to an interglacial climate similar to that of the present. Such a pattern is of a world hunting for a cooler equilibrium state only to cross a threshold which switches back to its warmer state, only for the cycle to repeat itself again. At present we do not know the feedbacks and links that explain this pattern, but the ice sheets are likely to be involved in amplifying the relatively minor changes in solar radiation received by the Earth as a result of Croll–Milankovitch orbital 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".