Biodiversity and conservation of Lake Huron’s islands
Bibliographic record
Abstract
Lake Huron has the largest collection of freshwater islands in the world. These islands are a significant contributor to the biodiversity of the region. In this paper, we give preliminary results of a project that assembles mapping of over 23,000 islands and island groups and provides the most comprehensive biodiversity assessment of islands in Lake Huron to date. The number, extent and configuration of many islands, particularly small, low-lying systems, is very dynamic depending on lake-levels. Islands in Lake Huron can be divided into three general groups: 1) limestone and dolostone islands associated with and surrounding Manitoulin and Drummond Islands and the Bruce Peninsula, 2) dense archipelagos of small nearshore Precambrian Shield islands in eastern Georgian Bay and the North Channel and, 3) small groups of low-erodible islands in Saginaw Bay. All three of these island groups are important for supporting colonial nesting waterbirds, endemic species and communities, and migratory birds. Lake Huron islands have been somewhat buffered from anthropogenic change due to their isolation and therefore support a rich and diverse sets of species and communities. Primary threats to island communities include development and invasive species. Threats are generally greater in many of the southern island regions where fewer islands are protected. Results from this project can be used to set priorities for conservation of key sites with high biodiversity values and conservation urgency.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".