Bibliographic record
Abstract
Embleton‐Hamann, C. and Slaymaker, O., 2012. The Austrian Alps and paraglaciation. Geografiska Annaler: Series A, Physical Geography, 94, 7–16. doi:10.1111/j.1468‐0459.2011.00447.xABSTRACTThere is some confusion in the geomorphological literature with respect to the usage of the term ‘paraglacial’. We review the meaning of the term as defined in the Anglo‐Canadian literature between 1972 and the present. We then show that many of these ideas were implicit in the early‐twentieth‐century German literature but were never, to our knowledge, synthesized into an overarching framework for the study of post‐glacial glaciated landscapes. It was not until the end of the twentieth century that the paraglacial model was directly applied to the interpretation of the European Alps. The first decade of the twenty‐first century has seen a growing appreciation and some critique of that model in research in the Austrian Alps. The post‐glacial glaciated landscape is interpreted as a landscape of transition between the full glacial of the Last Glacial Maximum and the present almost entirely deglaciated landscape. It provides a conceptual framework and a challenge to determine exactly how far any specific glaciated landscape has evolved in response to non‐glacial processes and whether it remains a disturbance regime landscape.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".