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Record W3187387078 · doi:10.25518/2295-8010.1740

Evaluation of an Acacia mangium Provenance Trial after Seven Years, on the Ibi - Batéké Plateau, Democratic Republic of the Congo

2021· article· en· W3187387078 on OpenAlexaff
Étienne Yusufu Kachaka, Vincent Poirier, Alison D. Munson, Damase P. Khasa

Bibliographic record

VenueTropicultura · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsMinistère des Ressources naturelles et des ForêtsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsAcacia mangiumProvenanceBiomass (ecology)AcaciaPlateau (mathematics)Soil waterCarbon fibersLitterSierra leoneBiologyAgronomyBotanyForestryEnvironmental scienceGeographyEcologyMathematics

Abstract

fetched live from OpenAlex

This study reports on the evaluation of 46 Acacia mangium provenances and varieties, which were planted in 2006 on the Ibi-Batéké Plateau, Democratic Republic of the Congo. After seven years, tree height and diameter, biomass and carbon stocks of the 46 Acacia mangium provenances, together with soil carbon and nitrogen concentrations, were compared with savannah soils in which Acacia was no present. Heights and diameters of 20 to 25 trees per provenance were measured. Carbon in the biomass was determined by the direct method. In total, 25 trees were harvested and weighed for each carbon compartment (leaves, branches, litter, trunks and roots). Ninety soil samples were collected at three different depths in the provenance plots and on the savannah and analyzed for their C and N concentrations. There were differences in height and diameter growth and in accumulated carbon among trees of different origins (provenances). Finally, soil C and N differed under different provenances, and with depth. Carbon and nitrogen tended to decrease with depth. The results of the study revealed better performance for provenances originating from Papua New Guinea, Australia, Malaysia, Vietnam, China, Fiji and the Philippines.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.999

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)0.0010.000

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 head0.017
GPT teacher head0.238
Teacher spread0.222 · 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.

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
Published2021
Admission routes1
Has abstractyes

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