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Cold-Climate Granite Landscapes

2006· book-chapter· en· W3104218470 on OpenAlexaboutno aff
Piotr Migoń

Bibliographic record

VenueOxford University Press eBooks · 2006
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsLandformGeologyBedrockPleistoceneEarth scienceCold climatePhysical geographyAridTerrainDesert climateGlacial periodGlacial landformMass wastingGeomorphologyPaleontologyGeographyMoraineClimatologySediment

Abstract

fetched live from OpenAlex

Inselbergs, tors, boulder fields, and pediments are repetitive landforms of many low- to mid-latitude granite landscapes, whether in humid or in arid environments. Although there have been attempts to link these landforms to certain specific climatic environments, their actual distribution, as shown in the preceding chapters, speaks clearly for minor climatic control in their development. Therefore, identification of a ‘typical’ granite rainforest, or savanna, or desert landscape does not seem possible. Each of these environments is known to host a variety of distinctive landscapes supported by granite, which will be explored in the next chapter. Likewise, cold environments in high latitudes have long been considered as having a very distinctive geomorphology, in which the factor of rock control matters little, but repeated freezing and thawing is critical. This view is difficult to maintain any longer, especially in the light of recent progress in periglacial geomorphology. The effects of glaciation are more evident, but even there the role of bedrock must not be neglected and formerly glaciated granite terrains do show certain specific features. Many granite terrains are located in cold environments, or have experienced cold-climate conditions in the relatively recent past of the Pleistocene. Therefore, it is reasonable to expect that their geomorphic evolution has been influenced by a suite of surface processes characteristic of such settings, collectively termed as ‘periglacial’. Present-day periglacial conditions typify such granite areas as the uplands of Alaska, Yukon, and the northern Rocky Mountains, much of the Canadian Shield, coastal strips of Greenland, northern Scandinavia, extensive tracts of Siberia, and the Tibetan Plateau. Granite areas located further south, in the British Isles, the Iberian Peninsula, the Massif Central, the Harz Mountains, and the Bohemian Massif, were affected by periglacial conditions for most of the Pleistocene. In fact, the most elevated parts of these mountains and uplands experience a mild periglacial environment even today and winter temperatures may remain below 0°C for weeks. The efficacy of present-day frost action is however limited by the insulating snow cover. Some of the granite areas of the southern hemisphere are, or were, within the periglacial realm too.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.025
GPT teacher head0.183
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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