Latitude matters: an examination of behavioural plasticity in dietary traits amongst extant and Pleistocene <i>Rangifer tarandus</i>
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
The geographical distribution of species affects their dietary traits relative to resources available in different latitudes. Dietary traits of Rangifer tarandus , a species with a wide geographical distribution, were investigated using tooth mesowear and microwear methods in eight extant populations from Canada. The data show a latitudinal shift corresponding to a vegetational gradient from the taiga to the tundra, i.e. an increase of lichen consumption from the low to the high latitudes. This pattern is also evidenced in the Pleistocene fossil record of Europe where R. tarandus populations from low latitude localities show a lower consumption of lichen than at higher latitudes.
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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 | 0.001 |
| 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