Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In contrast to the desolate environments that characterize much of the Arabia’s surface, the surrounding waters are home to a high level of biological diversity, including hundreds of species of fish. This is particularly true of the seas around the Musandam Peninsula of far north-eastern Arabia, where shallow gulf waters give way to open ocean. This chapter provides an inventory, description and analysis of fish names in Kumzari, an endangered language spoken in a handful of towns and city neighbourhoods in the wider region. The scope of fish as a semantic category is first delimited, followed by comments on the defining and labelling of fish species. The central section of the article proposes a typology of Kumzari fish names based on factors including association with other species, descriptions of their physical appearance and other, more complex kinds of descriptive labels. The article closes with reflection on fish names in their wider linguistic context: structural characteristics, use of fish names elsewhere in the lexicon, and the relevance of fish names for understanding the history of the Kumzari language. An explanatory lexicon of the 198 fish names in the data is provided as an appendix.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it