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Record W642082498

The Impact of Cattle Grazing on Aspen Regeneration on Crown Lands in Western Manitoba

2009· article· en· W642082498 on OpenAlexaboutno aff
J. Renton, A. Park, Richard Westwood

Bibliographic record

VenueMspace (University of Manitoba) · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
Fundersnot available
KeywordsCrown (dentistry)GrazingRegeneration (biology)Cattle grazingForestryEnvironmental scienceAgroforestryNatural regenerationGeographyAgronomyBiology
DOInot available

Abstract

fetched live from OpenAlex

In North America there has been an increasing appreciation for the value of trembling aspen as a source of timber (Populus tremuloides Michx). Moreover, aspen stands and the understory vegetation that they support also provide valuable forage for livestock and wildlife. Timber harvest and cattle grazing may occur on the same land base, although usually not simultaneously. The purpose of this study was to determine the affects of cattle grazing in post-harvest aspen stands in western Manitoba. In this study, grazed and non-grazed sites are compared to assess the effects of cattle grazing on stem density, tree health, and species diversity in the understory plant community across a seven-year chronosequence of harvests. Environmental data were collected to complement the biological data including soil compaction, soil texture, moisture regime and grazing pressure. Non-grazed sites in the oldest harvests had taller stems and significantly higher stem densities of aspen and all other tree species (p<0.1). Trees in grazed plots also exhibit poorer tree health characteristics than those in the non-grazed plots.

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 score0.563
Threshold uncertainty score0.868

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.035
GPT teacher head0.253
Teacher spread0.218 · 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
Published2009
Admission routes1
Has abstractyes

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