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Record W2170007748 · doi:10.1639/079.030.0303

Increasing Accessibility to Lichen Monitoring in Kejimkujik National Park and National Historic Site, Nova Scotia, Canada

2013· article· en· W2170007748 on OpenAlexaffabout
Jessica Ann Cosham, R. Troy McMullin

Bibliographic record

VenueEvansia · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNational parkLichenNova scotiaGeographyBioindicatorEnvironmental monitoringEnvironmental resource managementGlossaryEnvironmental protectionEcologyEnvironmental planningForestryEnvironmental scienceArchaeologyBiology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.244
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2013
Admission routes2
Has abstractyes

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