Bibliographic record
Abstract
Amphibians are highly adapted for life in wetland habitats. They form a major component of wetland faunas, and being both prey and predator, they are important in ecosystem functioning. Wetlands provide aquatic habitats that amphibians require for breeding, development, foraging, hibernation and refuge, and they form an interface with essential adjacent upland habitat. The size and type of wetlands as well as their spatial configuration and local structural characteristics are important features of these habitats for amphibian use. Because of their dependence on water, use of both aquatic and terrestrial habitat, permeable skin, and other biological characteristics, amphibians are considered to be excellent indicators of ecosystem health. Amphibians have a tremendous diversity of natural history characteristics and species differ in their patterns of habitat and microhabitat selection. Over 30 species of amphibians occur in wetlands within the Great Lakes Basin and an increasing trend in species richness exists from north to south across the region. Since European settlement, this region has lost over 50% of its wetlands. Loss rates of coastal and inland wetlands exceed 90% in some areas. Many restoration efforts are underway across the region but losses still exceed gains. No species have been extirpated from the entire basin but numerous local extirpations have occurred. However, nearly half of the species are officially designated as being of conservation concern somewhere in the basin. A more realistic estimate suggests that at least 2/3 of species are of concern. Habitat loss is reported as the primary cause of decline for 60% of species and habitat degradation by pollution is cited for 43% of the fauna. Considering the extent of wetland loss across the basin it seems reasonable to assume a similar magnitude of amphibian population loss. The current conservation status of amphibians indicates that Great Lakes wetlands are unhealthy ecosystems.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".