Increasing Accessibility to Lichen Monitoring in Kejimkujik National Park and National Historic Site, Nova Scotia, Canada
Bibliographic record
Abstract
Lichens, the proverbial “canaries in the coal mine”, are useful bioindicators due to their sensitivity to environmental changes. In 2006, a protocol was developed at Kejimkujik National Park and National Historic Site in Nova Scotia, Canada that used lichens to monitor ecological integrity and air quality within the park; assessments are ongoing every five years. There are currently no identification tools for park staff to conduct the monitoring process that specifically target the species being assessed. Here we present tools for the identification of the 50 lichen species used in the monitoring program at Kejimkujik. A taxonomic key, photographs of each species and an illustrated glossary are presented. While these tools are intended for individuals unfamiliar with lichens, some basic training to use the key is required. Park staff can use these aids to continue the monitoring protocol at Kejimkujik independently. With some modifications the same tools could serve as a template for other monitoring initiatives in the region.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".