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Record W4233537469 · doi:10.1139/x99-257

Establishment and growth in seedlings of<i>Fagus sylvatica</i>and<i>Quercus robur</i>: influence of interference from herbaceous vegetation

2000· article· en· W4233537469 on OpenAlexvenueno aff
Magnus Löf

Bibliographic record

VenueCanadian Journal of Forest Research · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
FundersSNS Nordic Forest ResearchSveriges Lantbruksuniversitet
KeywordsBeechFagus sylvaticaSeedlingQuercus roburFagaceaeGrowing seasonAgronomyShootBotanyVegetation (pathology)BiologyEnvironmental scienceHorticulture

Abstract

fetched live from OpenAlex

The interference from natural vegetation on the establishment and growth in Fagus sylvatica L. and Quercus robur L. was studied on an open site starting from bare soil. Four treatments were applied: herbicide, herbicide plus fertilization, mowing, and untreated control. Seedlings of beech and oak were spring planted side-by-side in two subsequent years and monitored through the 1995, 1996, and 1997 growing seasons. Interference had a strong negative influence on the seedling shoot dry mass, leaf area, relative diameter growth, leaf nitrogen concentration, and leaf water potential and conductance. Oak had a shorter period of transplanting shock, a higher relative growth rate during interference from vegetation, and deeper roots than beech. Therefore, oak is more easily established than beech, which initially may need more intense site preparation. Neither fertilization compared with vegetation control only, nor mowing compared with untreated control, influenced seedling growth. Low soil water potential had a strong influence on seedling growth, although the competing vegetation at the same time reduced light, soil temperature, and the soil nitrogen concentration.

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 score0.008
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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
Published2000
Admission routes1
Has abstractyes

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