MétaCan
Menu
Back to cohort
Record W2935958846 · doi:10.22621/cfn.v132i3.1988

Use of stabilized thaw slumps by Arctic birds and mammals: evidence from Herschel Island, Yukon

2019· article· en· W2935958846 on OpenAlexafffundvenueabout
Heather Cray, Wayne H. Pollard

Bibliographic record

VenueThe Canadian Field-Naturalist · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcGill UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaArcticNet
KeywordsTundraArcticPloverEcologyPermafrostSlumpHabitatThermokarstGeographyBiology

Abstract

fetched live from OpenAlex

As evidenced by animal sign (scat, active nests, nesting materials, rodent runways) observed across five stabilized retrogressive thaw slumps and two areas of undisturbed upland tundra, Arctic birds and mammals on Herschel Island, Canada, use stabilized thaw slumps differently than undisturbed tundra. Rodent winter nests and scat were found exclusively in undisturbed tundra and at a 250-year-old stabilized thaw slump site, whereas rodent runways and Semipalmated Plover (Charadrius semipalmatus) nests were found exclusively at 10- and 20-year-old stabilized thaw slump sites. Bird scat was found in each tundra type, but was most common in the youngest sites, and the number of observations decreased with increasing site age. Caribou (Rangifer tarandus granti) scat was found at all sites, whereas Muskox (Ovibos moschatus) scat was not found at 20-year-old sites and was most common in undisturbed tundra. To our knowledge, these observations are the first examples of birds and mammals using stabilized thaw slump habitat of different ages, and they provide new avenues of research for Arctic wildlife biologists concerned with the adaptation of these animals to permafrost disturbance and the resulting changes in vegetation cover.

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)0.000
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 score0.606
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.240
Teacher spread0.191 · 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

Citations3
Published2019
Admission routes4
Has abstractyes

Explore more

Same venueThe Canadian Field-NaturalistSame topicClimate change and permafrostFrench-language works237,207