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Record W2086016537 · doi:10.1139/x01-151

Subalpine forest damage from a severe windstorm in northern Colorado

2001· article· en· W2086016537 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbies lasiocarpaPinus contortaCanopyBoiler blowdownBasal areaWindthrowEnvironmental scienceSubalpine forestForestryStormDisturbance (geology)Picea engelmanniiAtmospheric sciencesEcologyMontane ecologyBiologyGeographyMeteorologyGeology

Abstract

fetched live from OpenAlex

As windstorm intensity increases above some threshold, disturbance spread and damage patterns are expected to be less strongly shaped by preblowdown forest composition and structure than by the pattern of the storm itself. We examined this generalization by analyzing differences in wind damage among tree species and stands following a severe blowdown in 1997 affecting over 10 000 ha of subalpine forest in the Routt Divide area of northern Colorado, U.S.A. Individual tree traits such as species, height, and status as standing dead or alive strongly influenced the amount and type (uprooting vs. snapping) of wind damage. Populus tremuloides Michx. exhibited much less uprooting and overall damage than the conifers. Among the canopy trees of the conifer species, Pinus contorta Dougl. ex. Loud and Abies lasiocarpa (Hook.) Nutt. sustained the lowest and highest rates of snapping, respectively. Standing dead conifers were more likely to be snapped than uprooted, and taller trees were more likely to be damaged than shorter trees. Stand-level characteristics such as stand density, amount of dead basal area, and species composition were predictive of the amount of wind damage for areas of moderate- but not high-severity blowdown. Even in such an extreme windstorm as the Routt blowdown, which had estimated wind speeds of 200–250 km/h, individual tree attributes and stand-level characteristics significantly influenced the severity and type of wind damage.

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)0.001
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 score0.954
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.272
Teacher spread0.234 · 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