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Record W4392461475 · doi:10.15560/20.2.279

Vascular plant, bryophyte, and lichen biodiversity of Agguttinni Territorial Park, Baffin Island, Nunavut, Canada: an annotated species checklist of a new Arctic protected area

2024· article· en· W4392461475 on OpenAlexafffundabout
Lynn J. Gillespie, Paul C. Sokoloff, Geoffrey A. Levin, Jennifer Doubt, R. Troy McMullin

Bibliographic record

VenueCheck List · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsCanadian Museum of Nature
FundersCanadian Museum of NaturePolar Knowledge CanadaUniversité de MontréalSmithsonian Institution
KeywordsLichenBryophyteChecklistVascular plantArcticGeographyBiodiversityThe arcticEcologyMarine protected areaEnvironmental protectionOceanographyBiologyGeologySpecies richnessHabitatPaleontology

Abstract

fetched live from OpenAlex

Agguttinni Territorial Park is a large, newly established park on the east-central coast of Baffin Island in Nunavut, Canada. Previous knowledge of the plant and lichen biodiversity was limited and based mostly on collections made during the 1950 Baffin Island Expedition. We conducted a floristic inventory of the park in 2021 and re-examined previous collections. We recorded 141 species of vascular plants belonging to 25 families, 69 species of bryophytes in 27 families, and 93 species of lichens in 23 families. Most of the vascular plant and bryophyte species are new records for the park area, and some vascular plants, bryophytes, and lichens are newly reported for Baffin Island, Nunavut, or the Canadian Arctic or represent significant range extensions. Vascular plant species diversity varied greatly among localities, with inland valleys at the heads of fiords showing highest diversity and interior rocky barrens showing the lowest.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.206
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes3
Has abstractyes

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