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Record W3113767870 · doi:10.5539/jps.v10n1p1

Effect of Thinning on Pericopsis elata (Harms) Meeuwen (Fabaceae) Found in Forest Plantations in the East and South Regions of Cameroon

2020· article· en· W3113767870 on OpenAlexvenueno aff
Jean Lagarde Betti, Ferdinand Kemkeng, Jules Romain Ngueguim, Joseph Ambara, Maturin Tchatat

Bibliographic record

VenueJournal of Plant Studies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
FundersInternational Tropical Timber OrganizationEuropean Commission
KeywordsThinningBasal areaForestryFabaceaeHorticultureMathematicsBiologyBotanyEnvironmental scienceAnimal scienceGeography

Abstract

fetched live from OpenAlex

This paper assesses the response of Pericopsis elata trees to silvicultural operations conducted in abandoned plantations settled between 1972 and 1975 in the East and South regions of Cameroon. Trees quality and DBH were evaluated before and 6 years after 2009 thinning. The silvicultural treatment of thinning improved the quality (physiognomy), the annual diameter increment and the stand basal area of trees. The average percentage of winding trees dropped from 82.8% in 2009 before thinning to 44.1%, six years later after thinning (2015). The most important average diameters were observed in thinned plots (27.3 ±10.4 cm - 30.5 ±10.0 cm) compared to non-thinned plots (22.9±13.2 cm-23.3±10.8 cm). Thinned plots gained at least 6 cm in diameter in 6 years, which is trice compared to the 2 cm observed in the non-thinned plots. The average annual diameter increment was 0.45 cm/year in thinned plots against 0.34 cm/year in non-thinned plots in the same period. Thinned plots have gain at least 6 m²/ha in the stand basal area against 1 m²/ha for non-thinned plots.

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)0.000
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 score0.056
Threshold uncertainty score0.112

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.065
GPT teacher head0.266
Teacher spread0.201 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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