MétaCan
Menu
Back to cohort

‘‘Silver Sagebrush Community Associations in Southeastern Alberta, Canada.’’ Rangeland Ecology & Management 58:400-405

2006· article· en· W2799310950 on OpenAlexaffabout
Cameron L. Aldridge, Mark S. Boyce

Bibliographic record

VenueJournal of Range Management · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsAlberta Conservation AssociationUniversity of Alberta
Fundersnot available
KeywordsHabitatRangelandGeographyWildlifeEcologyEndangered speciesWildlife refugeGrousePopulationAbundance (ecology)Wildlife managementBiology

Abstract

fetched live from OpenAlex

Understanding the distribution and abundance of habitat and resources is an important issue in wildlife conservation and will advance understanding of wildlife habitat relationships (Morrison 2001). Jones et al. (2005) developed a vital habitat layer, describing the distribution of silver sagebrush (Artemisia cana Pursh) in southeastern Alberta, Canada, and identifying relationships between sagebrush characteristics and physiographic parameters. This paper adds greatly to our understanding of poorly-studied silver sagebrush communities and as Jones et al. (2005) point out, this is an important first step in developing management plans for sage-grouse (Centrocercus spp.) recovery. This product has recently been used to understand sage-grouse habitat relationships, linking habitat to the viability of the endangered Alberta greater sage-grouse (Centrocercus urophasianus) population (Aldridge 2005).

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 score0.014
Threshold uncertainty score0.051

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Range ManagementSame topicRangeland and Wildlife ManagementFrench-language works237,207