Hydrogeomorphology and steep creek hazard mitigation lexicon: French, English and German
Bibliographic record
Abstract
Geoscientists, researchers and engineers study and work on similar projects all over the world. The exchange of information between colleagues of different countries who work on homologous projects or in similar fields requires a common technical vocabulary. Differences in the usage of technical terms and their varying definitions in different regions of the world may constrain the transfer of knowledge, for example in guidelines. Translations of technical papers and of presentations are particularly complicated and troublesome. Moreover, writers waste valuable time when they try to find proper technical terms in a different language. This is currently the case in the fields of fluvial geomorphology and steep creek hazard mitigation since several countries are active in these domains. Papers, guidelines, and policies are published in several languages, such as Japanese, Italian, French, German, English, Korean, Chinese and Spanish. International delegates are also submitting papers to journals, presenting and participating at conferences that are predominantly in English. Finally, working groups with multinational participants have been formed to advance research and transfer of knowledge in fluvial geomorphology and steep mountain creek hazard mitigation. Therefore, standardization and better definitions of technical terms are required. We propose in this paper a lexicon of French, English and German technical terms, and their definitions, related to the fields of fluvial geomorphology and steep mountain creek hazard mitigation. This paper focuses on the most important terms. In the future, other languages and supplemental terms could be added to this document with the help of other contributors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".