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Record W2153910865 · doi:10.1139/x01-181

Fourteen-year growth response of young lodgepole pine to repeated fertilization

2002· article· en· W2153910865 on OpenAlexvenueno aff
Barbara E. Kishchuk, G. F. Weetman, R. P. Brockley, Cindy E. Prescott

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsBasal areaHuman fertilizationFertilizerAnimal sciencePinus contortaBiologyBotanyAgronomyEcology

Abstract

fetched live from OpenAlex

Four rates of N (0, 50, 100, and 150 kg·ha –1 ) with and without a fertilizer mix containing P, K, S, Ca, Mg, and micronutrients were applied to a stand of 8-year-old lodgepole pine (Pinus contorta var. latifolia Engelm.) in four applications during 7 years. Fourteen years after the first fertilization, mean tree basal area and volume were significantly increased in the treatments containing the two highest rates of N plus the fertilizer mix. Mean tree basal area was 38% greater and mean tree volume was 42% greater in the highest N (525 kg·ha –1 ) plus mix treatment than in the control treatment. Stand basal area increased 48% over the control in the highest N plus mix treatment. Mean tree basal area and volume were 27 and 25% greater than the control under the intermediate N rate (350 kg·ha –1 ) with mix, respectively. Height growth was not significantly increased by fertilization. Both higher rates of N (four applications of >100 kg·ha –1 ) and the fertilizer mix were required for significant growth responses to occur. Addition of N alone or mix alone had a negative effect on mean tree basal area and volume. Addition of higher N rates without the mix decreased foliar total S and SO 4 -S concentration and increased the N/S ratio. Addition of the higher rates of N without the mix aggravated slight K deficiencies. The responses to the higher N rates in combination with the fertilizer mix are mainly attributable to S.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.052
GPT teacher head0.282
Teacher spread0.230 · 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.

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

Citations49
Published2002
Admission routes1
Has abstractyes

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