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Record W2807737129 · doi:10.1093/njaf/20.1.5

Windthrow After Shelterwood Cutting in Balsam Fir Stands

2003· article· en· W2807737129 on OpenAlex

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.

Bibliographic record

VenueNorthern Journal of Applied Forestry · 2003
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWindthrowBalsamAbies balsameaEnvironmental scienceDouglas firForestryGeographyHorticultureBiology

Abstract

fetched live from OpenAlex

Abstract The use of partial cutting in balsam fir stands has been greatly restricted by the fear of windthrow. This applies to shelterwood cutting, for which very little quantitative information on windthrow is available. This study was conducted in 50-yr-old balsam fir stands. The aim of the study was to quantify windthrow losses associated with three patterns of seed cuts. The study consists of five replicates of four treatments: uncut control, uniform shelterwood, group shelterwood, and strip shelterwood. Complete windthrow monitoring was performed at 2, 4, and 6 yr after cutting. The effect of treatment, wind exposure, and stand characteristics was assessed after 6 yr. A simulation with the ForestGales model was conducted to better understand the seed cut pattern effect in identical stands. Results showed that a shelterwood method involving a low intensity seed cut can be applied in relatively sheltered balsam fir stands. Topographic exposure and stand characteristics did not contribute to the amount of windthrow observed. The major factor explaining the amount of windthrow seems to be the presence of adjacent cuts that funneled wind into the plots. North J. Appl For.20(1):5–13.

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)0.000
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 score0.014
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.190
Teacher spread0.185 · 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