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Record W6942251207 · doi:10.14288/1.0378267

Variation in Trembling Aspen and White Spruce Wood Quality Grown in Mixed and Single Species Stands in the Boreal Mixedwood Forest

2019· article· en· W6942251207 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsTaigaBorealSalicaceaeLigninPinus <genus>Yellow birchPicea abies

Abstract

fetched live from OpenAlex

The Canadian boreal forest is largely represented by mixed wood forests of white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx). In this study, a total of 300 trees originating from three sites composed of trembling aspen and white spruce with varying compositions were investigated for wood quality traits: one site was composed mainly of aspen, one mainly of spruce and a third was a mixed site. Four wood quality traits were examined: wood density, microfibril angle (MFA), fibre characteristics, and cell wall chemistry. Social classes were also determined for each site in an attempt to provide a more in-depth comparison. Wood density showed little variation among sites for both species, with only significant differences occurring between social classes. The aspen site showed statistically lower MFAs than the aspen from the mixed site, however, no differences were observed when comparing spruce. Fibre characteristics were higher in the pure species sites for both species. There were no differences in carbohydrate contents across sites, while lignin content varied. Overall, the use of social classes did not refine the characterization of sites.

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 score0.424
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.030
GPT teacher head0.242
Teacher spread0.211 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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