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Record W1989303789 · doi:10.5558/tfc77351-2

Productivity of aspen stands with and without a spruce understory in Alberta's boreal mixedwood forests

2001· article· en· W1989303789 on OpenAlexaffvenueabout
Daniel M. MacPherson, Victor J. Lieffers, Peter V. Blenis

Bibliographic record

VenueThe Forestry Chronicle · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUnderstoryBiomass (ecology)TaigaEnvironmental scienceBorealForestryProductivityAgronomySalicaceaeTree allometryWoody plantBiomass partitioningEcologyBiologyGeographyCanopy

Abstract

fetched live from OpenAlex

In northeastern Alberta, the current biomass and periodic annual biomass increment (PAI) was measured in 29 stands of maturing aspen (Populus tremuloides)-white spruce (Picea glauca), aged 48 to 105 years. Plots in pure aspen were paired with nearby plots of aspen growing on a similar landform but with a spruce understory. Biomass was estimated by diameter at breast height and allometric equations. Totalled over both species, there was 10.5 % greater PAI and 10.0 % greater biomass in the mixed plots than in the pure aspen plots. Pure aspen plots, however, had 12.9% greater aspen biomass and 25.2% greater aspen PAI than the aspen component of mixed plots. The apparent decline in productivity of aspen in the mixed stands, however, could not be related to the variation in spruce abundance in these mixed stands. Key words: mixed wood management, understory, spruce boreal mixed wood

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 score0.534
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.211
Teacher spread0.193 · 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

Citations79
Published2001
Admission routes3
Has abstractyes

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