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Record W4403667328 · doi:10.22621/cfn.v137i4.3057

Description of a relict aspen parkland-associated grassland in the Peace River region of British Columbia, Canada

2024· article· en· W4403667328 on OpenAlexaffvenueabout
N. Ruaraidh Sackville Hamilton

Bibliographic record

VenueThe Canadian Field-Naturalist · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsGovernment of British Columbia
Fundersnot available
KeywordsGrasslandGeographyArchaeologyForestryAgroforestryEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

The aspen parkland-associated grasslands of the Peace River region, British Columbia (BC), have been severely reduced in area, primarily because of agricultural and urban development. In this region, the species composition of plant communities is similar to that of prairie grasslands and is topographically influenced, occurring primarily on warm-aspect slopes along the Peace River and some of its tributaries. Historical records show that non-forested grass- and sedge-dominated plant communities occurred on flat and gently rolling terrain in a parkland ecosystem near what are now the communities of Dawson Creek and Fort St. John. The Peace grasslands are not represented in BC’s biogeoclimatic ecosystem classification, perhaps leading to their neglect in regional natural resource management and conservation planning. Here, I describe the vascular plant community of a level-terrain relict aspen parkland-associated grassland in the Peace River region. Its species composition differs from nearby warm-aspect grasslands and includes provincially listed plant species. Increased awareness of grassland communities may support conservation, ecosystem restoration, and climate change adaptation in the southern boreal region of BC.

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 score0.013
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.011
GPT teacher head0.187
Teacher spread0.176 · 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
Published2024
Admission routes3
Has abstractyes

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