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Record W2104064813 · doi:10.1080/02827580510008356

Silvicultural options to promote seedling establishment on <i>Kalmia</i>–<i>Vaccinium</i>-dominated sites

2005· article· en· W2104064813 on OpenAlexafffundabout
Nelson Thiffault, Brian Titus, Alison D. Munson

Bibliographic record

VenueScandinavian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversité LavalCanadian Forest ServiceNatural Resources CanadaMinistère des Ressources naturelles et des Forêts (Québec)
FundersMinistère des Ressources Naturelles et de la FauneFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsScarificationSeedlingBiologyAgronomySowingBotanyEricaceaeHorticultureGermination

Abstract

fetched live from OpenAlex

Seedling growth is often hampered on sites dominated by Kalmia angustifolia. In June 2000, a trial was established on a clear-cut site in Quebec, Canada, with a high cover of Kalmia and Vaccinium species. The objectives were to evaluate how soil scarification and fertilization at the time of planting influence early growth and establishment of black spruce [Picea mariana (Mill.) BSP] and jack pine (Pinus banksiana Lamb.) seedlings. During the first 2 years, scarification reduced Kalmia cover three-fold and doubled the distance from seedlings to the nearest Kalmia stem. Scarification did not increase soil-extractable NH4-N concentration, and reduced soil potassium, calcium and magnesium. Scarification had no effect on seedling water stress. Seedling growth improved and foliar nutrient concentrations were generally higher in scarified plots than in unscarified control plots. No differences were observed between single- and double-pass scarification for any variables except for ground-level stem diameter of seedlings, which was greater with double-pass scarification (12.1 vs 13.1 mm). Spot fertilization increased seedling growth and foliar nitrogen concentrations. Jack pine growth was greater than black spruce growth, an effect enhanced when seedlings were fertilized.

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)0.001
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 score0.087
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.326
Teacher spread0.287 · 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

Citations48
Published2005
Admission routes3
Has abstractyes

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