Effective dispersal of large seeds by Baird's tapir: a large-scale field experiment
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
Even though the full process of seed dispersal is the combination of movement mode and distance, deposition, successful germination and survival (Nathan 2006, Westcott et al . 2005), relatively few studies have documented the role of mammals as facilitators of germination and survival (Paine & Harms 2009). In particular, the effectiveness of large terrestrial mammals (>50 kg) as effective dispersers of large seeds is poorly known, but has been linked to the treatment of the seeds in their digestive system, the deposition of viable seeds in nutrient-rich environments (faeces) and favourable sites. Other aspects related to long-distance movements, defecation patterns and home-range size are frequently cited as factors that favour the deposition of seeds far from parent trees, which is expected to reduce predation and intraspecific competition, and enhance fitness (Schupp et al . 2002). We addressed these issues through a large-scale field experiment.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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