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Record W1983060822 · doi:10.1139/x02-143

Terpenoids in the wood of Scots pine and Norway spruce seedlings exposed to ozone at different nitrogen availability

2002· article· en· W1983060822 on OpenAlexvenueno aff
Jarkko Utriainen, Toini Holopainen, Pirjo Kainulainen

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsScots pinePicea abiesLimoneneTerpeneChemistryBotanyNutrientNitrogenOzoneWoody plantPinaceaeTurpentineSoftwoodPinus <genus>HorticultureBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) seedlings were exposed to low-level ozone (O 3 ) in an open-air exposure system for three or two growing seasons, respectively. Simultaneously, seedlings were supplied with nutrient solution containing either optimum (control) nitrogen (N), 70% of optimum N (low N availability), or 150% of optimum N (high N availability). Carbon-based secondary compounds, e.g., terpenes and resin acids, were analysed from the stemwood. α-Pinene, 3-carene, and limonene + β-phellandrene were the major terpenes in pine wood, whereas α-pinene, β-pinene, and limonene + β-phellandrene dominated in the spruce wood. Palustric + levopimaric and abietic acids were the major resin acids in the wood of both species. Ozone exposure did not cause any remarkable changes in the concentrations and proportional quantities of terpenes and resin acids in the wood of either tree species. Nitrogen availability did not affect the concentrations of carbon-based secondary compounds either, and the effects on proportional quantities were slight and ambiguous with respect to N supply. We conclude that realistically elevated levels of O 3 do not have effects on concentrations of carbon-based secondary compounds of conifer wood and N availability might cause only slight changes in them. Therefore, our results do not directly support the carbon–nutrient balance hypothesis.

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)0.001
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 score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.054
GPT teacher head0.256
Teacher spread0.202 · 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

Citations25
Published2002
Admission routes1
Has abstractyes

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