Determining natal sources of capelin in a boreal marine park using otolith microchemistry
Bibliographic record
Abstract
The effectiveness of marine conservation areas are influenced by the structure of the food webs they encompass, including the population dynamics of potentially important forage species that occupy trophic positions between those of zooplankton and higher trophic levels. Capelin is a key forage species for marine mammals, seabirds, and fish in the Saguenay-St. Lawrence Marine Park (SSLMP, Canada), yet knowledge on its population dynamics is incomplete. In particular, the natal sources sustaining this critical forage species within the conservation area remain unknown. Otolith microchemistry as an index of natal habitat was investigated, including measures of boron, barium, iron, magnesium, manganese, and strontium over the protracted spawning season of capelin. Otolith microchemistry indicated that the principal natal source of 1+ capelin found within the SSLMP was located in the St. Lawrence estuary, outside the conservation area boundaries. To ensure the sustainability key forage species within the conservation area, larger scale long-term management strategies are necessary to encompass ecological processes related to capelin that extend beyond the conservation area boundaries.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".