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Record W2127197729 · doi:10.1139/x05-196

Heartwood extractives in larch and effects on X-ray densitometry

2005· article· en· W2127197729 on OpenAlexvenueno aff
Michael Grabner, Rupert Wimmer, Notburga Gierlinger, Robert Evans, Geoffrey M. Downes

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersInstitut National de la Recherche AgronomiqueCommonwealth Scientific and Industrial Research Organisation
KeywordsLarchLarix kaempferiHot water extractionSoftwoodBotanyChemistryExtraction (chemistry)HorticultureBiologyChromatography

Abstract

fetched live from OpenAlex

The genus Larix is exceptional for its high content of extractives in the heartwood, with the dominating component arabinogalactan found abundantly in cell lumens of tracheids. On samples prepared from 100 European larch (Larix decidua Mill.) and hybrid larch (L. decidua × Larix kaempferi (Lamb.) Carr.) trees, extractive contents and wood density were measured using X-ray densitometry. A strong relationship between the amount of hot water extractives and the loss of density owing to the extraction process was found. Prior to extraction, increasing extractive content went hand-in-hand with higher wood density. At the heartwood–sapwood boundary, the density level dropped. After acetone and hot water extraction, the drop was no longer visible. Without proper consideration of the extractives in larch growth sites, comparisons in wood quality studies looking at wood density differences may become faulty, breeding studies could lead to incorrect selection strategies, and tree-ring studies may not deliver the expected climatic signals. Hence, hot water extractions should take place prior to radiation exposure.

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 score0.644
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.315
Teacher spread0.278 · 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

Citations39
Published2005
Admission routes1
Has abstractyes

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