Diet of the crest-tailed mulgara (Dasycercus cristicauda) in the Strzelecki Desert
Bibliographic record
Abstract
A population of the crest-tailed mulgara (Dasycercus cristicauda) was recently located in the southern Strzelecki Desert in 2015. We analysed the diet of this population from scats (n = 87) collected over two sampling periods in 2016. Beetles were the most favoured food item, followed by spiders, ants and the small mammal Notomys fuscus. Within the beetles, ground beetles (Carabidae) and darkling beetles (Tenebrionidae) were the most frequently consumed. Dasycercus cristicauda appeared to exhibit a seasonal shift in prey consumption, moving from vertebrates in July 2016 to invertebrates in November 2016, while also consuming a wide and varied range of prey, even including rabbits in their diet in July 2016. The flexible diet observed in Dasycercus cristicauda may be a response to the fluctuating availability of food found in desert environments.
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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".