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Record W1970906440 · doi:10.1139/x04-105

Early growth of white spruce underplanted beneath spaced and unspaced aspen stands in northeastern British Columbia

2004· article· en· W1970906440 on OpenAlexvenueaboutno aff
Philip G. Comeau, Cosmin N. Filipescu, Richard Kabzems, Craig DeLong

Bibliographic record

VenueCanadian Journal of Forest Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsThinningUnderstoryBasal areaSowingSeedlingForestryHuman fertilizationSilvicultureBiologyPicea abiesAgronomyVegetation (pathology)HorticultureBotanyEnvironmental scienceCanopyGeography

Abstract

fetched live from OpenAlex

We examined the growth of white spruce planted underneath a 33-year-old stand of trembling aspen following thinning and fertilization. Thinning the stand to 2000 stems·ha –1 resulted in increased light reaching spruce seedlings and significant increases in height and diameter growth of seedlings over that observed in either the unspaced or 3000 stems·ha –1 treatments. Fertilization (applied 3 years prior to planting) stimulated development of understory vegetation and did not benefit the planted spruce. While growth was improved by thinning, the benefits of the thinning treatment to establishment of white spruce appeared to be small, and amounted to increasing seedling height from 62 cm (unthinned) to 73 cm (thinned to 1000 or 2000 stems·ha –1 ) at the end of 5 years. Results indicated that when stands are thinned for the purpose of accelerating growth rates of underplanted spruce, residual basal areas above 25 m 2 ·ha –1 should be retained to suppress growth of understory vegetation. Comparison of height at age 5 for seedlings planted under untended stands at Fort Nelson with three sites near Dawson Creek indicated no differences between locations, when height at the time of planting was included as a covariate.

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)0.001
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 score0.141
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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.

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

Citations17
Published2004
Admission routes2
Has abstractyes

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