MétaCan
Menu
Back to cohort
Record W2034523925 · doi:10.2193/2007-079

Determining Sustainable Levels of Cumulative Effects for Boreal Caribou

2008· article· en· W2034523925 on OpenAlex
Troy C. Sorensen, Philip D. McLoughlin, Dave Hervieux, Elston Dzus, J. W. Nolan, B. B. Wynes, Stan Boutin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Wildlife Management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCollège BoréalAlberta Pacific Forest IndustriesUniversity of AlbertaGovernment of Alberta
Fundersnot available
KeywordsBorealEcologyHabitatThreatened speciesRange (aeronautics)Cumulative effectsPopulationGeographyWoodland caribouEnvironmental scienceDisturbance (geology)Vital ratesHabitat destructionPopulation growthPhysical geographyBiologyDemography

Abstract

fetched live from OpenAlex

Abstract: Direct and indirect effects of industrial development have contributed, in part, to the threatened status of boreal ecotype caribou ( Rangifer tarandus caribou ) in Alberta and Canada. Our goal was to develop a model that would allow managers to identify landscape‐scale targets for industrial development, while ensuring functional habitat for sustainable caribou populations. We examined the relationship between functional habitat loss resulting from cumulative effects of natural and anthropogenic disturbance, and the rate of population change (Λ) for 6 populations of boreal caribou in Alberta, Canada. We defined functional habitat loss according to 2 variables for which we had a priori reasons to suspect causative associations with Λ: 1) percentage area of caribou range within 250 m of anthropogenic footprint, and 2) percentage of caribou range disturbed by wildfire within the last 50 years. Multiple regression coefficients for both independent variables indicated significant effects on Λ. The 2‐predictor model explained 96% ( R 2 ) of observed variation in Λ among population units ( F 2,3 = 35.2, P = 0.008). The model may be used to evaluate plans for industrial development in relation to predicted wildfire rates and goals for caribou population growth rates.

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.

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)0.001
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 score0.447
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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