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Record W2003772248 · doi:10.1139/x08-165

Intensity of precommercial crop tree release increases diameter growth and survival of upland oaks

2009· article· en· W2003772248 on OpenAlexvenueno aff
Jeffrey S. Ward

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsCanopyCrown (dentistry)Stand developmentCompetition (biology)BiologyStanding cropAgronomyThinningCropTree canopyFagaceaeForestrySilvicultureBotanyHorticultureAgroforestryEcologyBiomass (ecology)Geography

Abstract

fetched live from OpenAlex

In 1988, seven study areas were established in Connecticut to examine the effects of precommercial crop tree release on development of sapling red oaks ( Quercus rubra L.) (n = 1250). Crown class at canopy closure, competition from adjacent trees for growing space and limited resources, and interaction of these factors were major determinants of survival, upper canopy persistence, and diameter growth over the 18 year period studied. Complete release from competition of neighboring trees, but not partial release, increased survival of intermediate and codominant stems. Complete release did not increase survival of oaks in the dominant crown class. Few intermediate and no suppressed oaks ascended into the upper canopy without crop tree release. Complete release doubled the proportion of codominant trees that remained in the upper canopy and increased the proportion of intermediates that ascended into the upper canopy. Complete release increased 18 year diameter growth only for dominant and codominant oaks. Because precommercial crop tree release simultaneously increases the probability that high-quality stems of desired species will be present in the mature stands and increases the diameter growth of those stems, this technique should be considered in stands with low oak densities.

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)0.001
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 score0.328
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.272
Teacher spread0.246 · 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

Citations37
Published2009
Admission routes1
Has abstractyes

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