Bibliographic record
Abstract
Abstract Permafrost geomorphology came of age in 1965–2000, evolving from a field-based subdiscipline largely based on qualitative observation to one of detailed process measurement, field experimentation, and analytical modelling. In this, the development of permafrost geomorphology exemplified the change in geomorphology as a whole. Fundamental advances were made in understanding the development of ice wedges and ice-wedge polygons and the genesis and growth of closed-system pingos, especially by J. Ross Mackay working in the continuous permafrost terrain of the western Canadian Arctic coastlands. Mackay also investigated moisture movement in relation to the ground thermal regime, which led to seminal insights regarding ground freezing, frost heave, near-surface ground ice development, and hummocky micro-relief. Others used these ideas to examine frost shattering of rocks and the development of sorted circles, as most well known from Svalbard. In the second half of the period, measurements of permafrost creep and deformation of hillslopes and rock glaciers were presented, complementing antecedent measurements of solifluction in the active layer. Significant investigations of thermokarst development foreshadowed the preoccupation with permafrost thaw that now gathers so much attention.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.007 | 0.001 |
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.
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".