Dunnville Marsh management plan
Bibliographic record
Abstract
The Dunnville Marsh property, situated at the mouth of the Grand River, was acquired from Canadian Pacific Rail Ltd. in early 1994. Its securement was made possible by the Nature Conservancy of Canada through funding provided from the Eastern Habitat Joint Venture of the North American Waterfowl Management Plan and the Great Lakes Cleanup Fund. The property, consisting of approximately 350 ha, contains marshlands, wetland swamps, agricultural fields, abandoned clearings and upland woodlands. The Grand River Conservation Authority was transferred ownership later in the same year. The overall guiding principle and goal for the property strives "to preserve the lands as a natural area for the conservation and management of waterfowl, other wildlife and the natural communities." Towards these ends, a "Management Committee" and has been working towards the preparation of this management plan. This plan represents a significant contribution by the members of the Dunnville Marsh Management Committee. This committee was formed in 1994 to make recommendations and provide technical expertise towards the future management of the property. The public has been invited as well to participate in the planning process. This plan formally recognizes the efforts of all partners and participants plus provides the basis and framework for future, cooperative management efforts.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.162 | 0.041 |
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".