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Record W7028932655

Impact of modified retention clearcuts on perimeter stands dominated by trembling aspens

2009· dissertation· en· W7028932655 on OpenAlexfundaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2009
Typedissertation
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsSnagThinningDebrisCoarse woody debrisPerimeterHydrology (agriculture)Dead tree
DOInot available

Abstract

fetched live from OpenAlex

This study examines post-harvest tree mortality following modified retention clear- cutting of aspen-dominated forests in Duck Mountain, Manitoba.Twenty-meter fixed radius plots were enumerated in undisturbed forest, and in 1,2,4, and 8 year old cutblocks.Bole cracking was more common along perimeter edges.Wind-thrown trees were most common on west-facing cutblock edges, intermediate on south and north edges, and least common on east edges.Most wind-throws resulted from winds from the north and west.Most wind-thrown aspen were stem snapped, but uprooting was more common in white spruce.The wind-throw mortality rate in undisturbed forest was2 treesftta/yr.This increased to 4-8 trees/halyr along cutblock edges.A substantial number of older snags were wind-toppled within a year following clearcutting.After eight years, total wind-throw mortality was twice that of undisturbed forest.A simple model successfully predicted temporal trends in coarse woody debris accumulation following clearcutting.ACKNOWLEÐGEMENTS

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 score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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 routes2
Has abstractyes

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