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Record W7140154696

Terrain Susceptibility to Windthrow of Trees in Subalpine Forests, Canadian Rockies

2019· dissertation· en· W7140154696 on OpenAlexaboutno aff
Paul Akhere Momodu

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
FundersDirectorate for Biological Sciences
KeywordsWindthrowMontane ecologyTerrainDisturbance (geology)Wind speedCanyonHydrology (agriculture)Drainage
DOInot available

Abstract

fetched live from OpenAlex

Windthrow is a natural disturbance that can result in significant impacts on forests. Modelling of basin-scale patterns of wind speed in subalpine forests of the Canadian Rockies and evaluation of terrain susceptibility to windthrow of trees in these forests have not previously been undertaken. The present study uses the numerical model, WindStation, to simulate wind speed patterns in two mountainous drainage basins in Kananaskis, Canadian Rockies. Locations and associated terrain characteristics where wind speeds for major wind events exceed the threshold of 42 m s-1 are evaluated. Results show that locations where wind speeds exceed the threshold for windthrow and are also treed are limited in spatial extent, occurring mainly at the upper parts of drainage basins close to the drainage divide. Understanding terrain susceptibility to windthrow provides important information about the types of disturbance that control forest dynamics in the subalpine forests of the Canadian Rockies.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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 teacher head, not a consensus.

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
Published2019
Admission routes1
Has abstractyes

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