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Record W2892094139 · doi:10.1093/forestry/cpy032

Ecology and management of northern red oak (Quercus rubra L. syn. Q. borealis F. Michx.) in Europe: a review

2018· review· en· W2892094139 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueForestry An International Journal of Forest Research · 2018
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStockingForestryPruningCompetition (biology)Crown (dentistry)GeographySoil waterAgroforestrySilvicultureEnvironmental scienceBiologyAgronomyEcology

Abstract

fetched live from OpenAlex

Abstract Northern red oak (Quercus rubra L. syn. Q. borealis F. Michx.) is a valuable broadleaved tree species originating from the eastern half of the USA and Canada. It was introduced to Europe in 1691 and currently covers over 350 000 ha, being found all over the continent, except the coldest part of Scandinavia. It is a fast-growing and valuable broadleaved tree due to its ecological characteristics, good wood properties and high economic value. Northern red oak prefers deep, loose, moderately humid and acid soils, without compact horizons and of at least moderate fertility. It does not grow well on dry, calcareous soils as well as waterlogged or poorly drained soils. It is either naturally regenerated using a group shelterwood system or planted using seedlings of European provenance, collected in certified seed stands. As northern red oak is light-demanding, its management should be ‘dynamic’ and includes heavy interventions (cleaning–respacing and thinning from above), in order to minimize crown competition between the final crop trees. These should produce large diameter trees for valuable end uses (e.g. veneer, solid furniture, lumber, etc.) within a rotation period generally of 80–100 years. The necessity for pruning (both formative and high) depends on the stand stocking at establishment, the subsequent silvicultural interventions as well as the occurrence of forking. The adaptation potential of northern red oak to predicted climate change, especially drought, seems to be higher than for European native oaks, the importance of the species is expected to increase in the future.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.826
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.107
GPT teacher head0.386
Teacher spread0.279 · 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