Bibliographic record
Abstract
This is the OBIS extraction of the Ocean Tracking Network and Dalhousie University (DAL) Inner Bay of Fundy Kelts, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=IBOFK). Abstract:The Inner Bay of Fundy (iBoF) population of Atlantic salmon is the only Designatable Unit listed as endangered under the Canadian Species at Risk Act. This population is genotypically distinct and unlike most salmon, is characterized by localized migrations within the inner bay instead of migrating to the Labrador Sea and beyond. The Coldbrook Biodiversity Center Live Gene Bank hatchery currently maintains this population by supplementing iBoF rivers that no longer produce wild salmon. Previous assessments of this stock have indicated high predation mortality, suggesting poor marine survival. In this study, we will work closely with the Coldbrook Center to tag and track Stewiacke River Atlantic Salmon (post-spawned) kelts to investigate marine survival, as well as habitat use and migration patterns. We will also tag smolts in the Debert River that were released from Coldbrook to rear in this river that forms part of the historic distribution. Kelts will be tagged with 69 kHz V13T and 180 kHz V9 tags in the spring and fall of 2024 and 2025 and will be tracked with the extensive array of receivers deployed from the Minas Basin out to the Gulf of Maine. Smolts will be tagged with 6mm predation tags and ID tags following capture by fyke net in the Debert River. These data will help us answer questions about whether iBoF salmon remain in the inner bay, key spatial areas used, how long they remain at sea, and predation mortality.
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 | 0.001 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.076 | 0.023 |
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".