Fisheries Centre research reports. Volume 20, number 2
Bibliographic record
Abstract
This report summarizes the existing knowledge on three ecosystems: Hudson Bay, Canada, Kaloko- Honokōhau, Hawai‘i, and the Antarctic Peninsula, Antarctica. Through the construction of ecosystem models representing these three regions, research from numerous aspects of each ecosystem are pieced together to present a holistic story. While we live in a rapidly changing world, it is important to remember there are many regions where we are still gaining an understanding of basic knowledge. Research on these ecosystems, from the Arctic to the tropics to the Antarctic, presents different levels of our knowledge. For the Arctic (Hudson Bay) the focus is identifying changes known to be occurring for certain species, and addressing the reasons for those changes in addition to the greater implications to the rest of the ecosystem. In the tropics (Hawai‘i) the construction of a model allows insight into structure and function of the ecosystem focusing on the role of an endangered species, the green sea turtle, and provides a baseline to assess potential future impacts on the ecosystem from coastal development. In the Antarctic (AntarAntarctic Peninsula) ecosystem, environmental changes are explored as they impact a key link in the food web. While the models presented address localized issues relating to very different regions of the world, the ultimate goal is the same; to increase our understanding of ecosystems as a whole and the different stressors related to each region. With this knowledge, we can formulate better questions for future research, assist in informing managers, and hopefully gain greater insights and understanding of the likely impact of future stressors.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.391 | 0.227 |
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".