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Record W383442182 · doi:10.1079/9780851996936.0157

An allometric-Weibull model for interpreting and predicting the dynamics of foliage biomass on Scots pine branches.

2003· book-chapter· en· W383442182 on OpenAlexaff
Richard A. Fleming, T. R. Burns

Bibliographic record

VenueCABI Publishing eBooks · 2003
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsCanadian Forest Service
Fundersnot available
KeywordsScots pineWeibull distributionAllometryBiomass (ecology)MathematicsStatisticsPinus <genus>BiologyEcologyBotany

Abstract

fetched live from OpenAlex

The foliar biomass dynamics on the branches of young, open-grown, Scots pine (Pinus sylvestris) in Sweden were modelled as functions of branch length and age. These dynamics are rooted in a biological foundation by assuming that foliage production depends allometrically on branch length and that foliage survival on a branch follows an age-dependent Weibull distribution. Like previously constructed descriptive models, the more process-based model developed here fitted the data well. In contrast to these purely descriptive models, however, this more process-based model demonstrated some predictive ability when extrapolated, and produced biologically meaningful parameter estimates.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2003
Admission routes1
Has abstractyes

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