Bibliographic record
Abstract
Abstract Luro, an Austroasiatic language of the Mon-Khmer group is spoken in the Teressa island of the Andaman and Nicobar group of islands in the Bay of Bengal, India. Luro is a critically endangered language spoken by less than 2,000 speakers ( Directorate of Census Operations 2011 ). The morphology of Luro is virtually undescribed in detail so far. The previous works are restricted to deRoepstorff (1875) , Cruz (2005) , Man (1889) and Rajasingh (2019) which are limited to wordlists and a partial dictionary. This is the first-ever account of word formation process in the language. Word formation processes include among others, compounding and derivation across grammatical categories. Incorporation is used in verb morphology. Although language does not have an extensive case marking system postpositions appear on some nouns optionally. Nouns are marked for duality and plurality but not for gender. Negation is indexed with pronoun morphology and participates in formation of antonyms. Kinship terminology and Number System have also been dealt with to represent diverse word formation processes. 1
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".