Bibliographic record
Abstract
The Peace Athabasca Delta (PAD) is the largest freshwater delta in North America, has been designated as a wetland for international importance and a UNESCO World Heritage Site. The PAD is located in northeastern Alberta and is home to numerous species of birds, mammals and fish. Additionally, the PAD is home to numerous Indigenous communities who have occupied the delta for generations, using its resources for sustenance. Lake whitefish are one key subsistence food source for Indigenous communities that live on the PAD. In recent years, Elders, Fishers and community members have noticed a decline in the meat quality of the lake whitefish, specifically meat that appears ‘mushier’. Residents of the communities are concerned with the ecological changes they currently see in the PAD (potentially due to human/industrial development upstream) and worry that if changes persist, the ecological health of the delta will deteriorate. The goal of this project was to continue the monitoring of lake whitefish in the PAD in collaboration with local Indigenous communities, the Government of Alberta, and Environment and Climate Change Canada (ECCC). Analyzing fish health can give an indication of overall aquatic health and provide information on whether the health of the lake whitefish is changing. Samples were collected in fall and winter, starting in 2020 until the present. My work focused on analyzing the fall 2021 - winter 2022 samples, to add this information to the fish monitoring efforts. The samples were collected and sent to our collaborators at ECCC, after which they were transported to Western University, where they were kept at –20C until analysis. At Western, I analyzed the sample levels of tissue water, protein, and lipid, following established protocols. The findings from the current research will be compiled with data from recent years and shared with community members to help the communities and research better assess the health of fish in the PAD.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".