Sizing up the ecological role of sharks as predators
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
Top predators and large-bodied megafauna are often the most affected elements of exploited ecosystems, both on land and in the sea; and the top-down control these predators exert on prey species can significantly alter community structure The loss of predation and the resultant indirect effects of mesopredator release and trophic cascades have resulted in widespread trophic downgrading of ecosystems For example, both the loss of wolves from Yellowstone National Park in the USA and declines in largebodied shark populations of the western North Atlantic Ocean have been reported to cause mesopredator release and trophic cascades Recently, much of the research focus has been on the response of prey to predators; here, we focus our attention on the ecological role of the predator. Despite some compelling and widely-cited case studies, our understanding of the dynamics of predators in regulating prey populations is still limited, yet predation is recognised as a key ecological and evolutionary process Particularly in the marine realm, gaining sufficient knowledge of large, highly mobile predators to define their roles is challenging. The widespread nature of these species makes them difficult to target, handle and experimentally manipulate for the purposes of research. Thus, defining the impacts of large marine predators is problematic.
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.
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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 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 it