Lake Winnipeg Basin Initiative Phase II Final Report, 2012/2013 to 2016/2017
Bibliographic record
Abstract
This report has been compiled to highlight the activities conducted during Phase II (2012-2017) of the Lake Winnipeg Basin Initiative (LWBI) of Environment and Climate Change Canada (ECCC). It contains an overview of the accomplishments achieved under each pillar of the LWBI: Science, Stewardship and Transboundary Partnerships. The Science section outlines the projects undertaken by ECCC scientists including a project overview, results and plans for future research. A full list of scientific publications can be found in Appendix B. The Stewardship section describes the LWBI’s grants & contributions program, including funding priorities, eligibility requirements and the application process. This report also describes the results achieved by these projects, with descriptions of each project highlighted in Appendix A. Finally, the Transboundary Partnerships section outlines the interjurisdictional and policy work carried out by ECCC in collaboration with a multitude of partners. Problems and solutions to the challenges facing Lake Winnipeg are interprovincial and international in scope. Any solutions for improving the health of the lake will take time and require the coordinated efforts of multiple stakeholders in the Lake Winnipeg Basin.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".