A new giant shrew rat (Rodentia, Muridae, Murinae) from Flores, Indonesia and a comparative investigation of its ecomorphology
Bibliographic record
Abstract
We describe a new genus and species of large-bodied murine from archaeological deposits at Liang Bua, a limestone cave in western Flores, East Nusa Tenggara, Indonesia.Among a large assemblage of murine remains, several mandibular elements recovered from mostly Holocene sediments show a distinct anatomy, with a long and robust jaw, massive proodont incisors, and relatively small molars.These morphological features are unusual among murines but most similar to terrestrial and carnivorous species of the Indo-Pacific, colloquially referred to as shrew rats (Philippines, Sulawesi) or moss mice (New Guinea), and indicate a potential carnivorous dietary adaptation, perhaps specializing in a vermivorous diet.The size of the mandible indicates that this murine is the largest shrew rat yet known.Although presumed extinct, targeted field research is needed to determine if this rat still lives on Flores today.Abstrak [Bahasa Indonesia].Kami mendeskripsikan genus dan spesies baru murine bertubuh besar dari deposit arkeologi Situs Liang Bua, sebuah gua kapur di Flores bagian barat, Nusa Tenggara Timur, Indonesia.Di antara himpunan besar sisa-sisa murine, beberapa elemen rahang bawah yang sebagian besar ditemukan dari sedimen Holosen menunjukkan anatomi yang berbeda, dengan rahang yang panjang dan kokoh, gigi seri proodont sangat besar, dan geraham yang relatif kecil.Ciri-ciri morfologi ini tidak biasa di antara murine, tetapi sangat mirip dengan spesies terestrial dan karnivora dari bahasa sehari-hari Indo-
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 | 0.001 | 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) | 0.001 | 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".