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Record W4281719335 · doi:10.3389/ffgc.2022.867247

Tree Growth, Foliar Nutrition, and Soil Properties in Mixtures of Lodgepole Pine and Sitka Alder in the Central Interior of British Columbia, Canada: 25-Year Results

2022· article· en· W4281719335 on OpenAlexaffabout
Paul Sanborn, Peter K. Ott

Bibliographic record

VenueFrontiers in Forests and Global Change · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsMinistry of ForestsUniversity of Northern British Columbia
Fundersnot available
KeywordsPinus contortaAlderAlnus glutinosaBotanyHorticultureBiologyForestryEnvironmental scienceAgronomyGeography

Abstract

fetched live from OpenAlex

Densities of naturally regenerated mixtures of lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) and Sitka alder [Alnus viridis subsp. sinuata (Regel) Á. Löve & D. Löve] were manipulated in 1995 at a site logged in 1987 in the central interior of British Columbia, Canada. Four levels of alder retention (0, 500, 1,000, and 2,000 clumps/ha) were combined with a uniform lodgepole pine density of 1,000 stems/ha across all treatments. After 25 years, effects of alder retention on lodgepole pine growth consisted of modest reductions in height and diameter increment, and treatment effects on soil nitrogen were confined to the forest floor organic horizons. Nutritional benefits of alder retention for lodgepole pine were not detected after year 6. The operational silvicultural implication of these findings is that only limited intervention to control Sitka alder in similar stands can be justified.

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 score0.094
Threshold uncertainty score0.190

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 studies0.0010.001
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 head0.007
GPT teacher head0.173
Teacher spread0.166 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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