Bibliographic record
Abstract
Nova Scotia supports an exceptionally high diversity of lichen species.The province's geographic position in the North Atlantic, and high coastline length in relation to area ratio, ensure a cool wet climate that is conducive to lichens and the development of lichen habitats, particularly in coastal forests (Clayden et al. 2011).Furthermore, Nova Scotia transcends the boundary between boreal and temperate forests, and therefore is colonized by lichen species either on the northern or southern limits of their geographic distribution (Davis and Browne 1996).Some examples include Boreal Felt Lichen, an endangered lichen at the southern extent of its range in North America and Vole Ears, an endangered lichen at the northern extent of its global range (Maass & Yetman 2002, Cameron et al. 2011).Many lichen species which are relatively common in Nova Scotia are rare and declining in the northeastern USA, and these are listed by Hinds & Hinds (2007).Our province has a disproportionately high number of nationally listed lichen species.Nine of the of 24 lichen species listed by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in Canada occur in Nova Scotia (COSEWIC 2019).Furthermore, roughly 10 percent of all the wildlife species listed provincially as At-Risk are lichens (Nova Scotia Department of Lands and Forestry 2019).Like many other organisms, the distribution of lichens is neither random nor even across the landscape in Nova Scotia.Most of the at-risk, rare or uncommon lichens in NS occur in specific habitats in association with other at-risk lichen species in spatially discrete localities (Cameron & Richardson 2006, Cameron & Neily 2008, McMullin et al. 2008).Lichens such as the Boreal Felt Lichen, tend be clustered, with some clusters having high populations (Cameron & Neily 2008, Cameron et al. 2013).
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 | 0.002 | 0.002 |
| 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".