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Record W2806018309 · doi:10.2989/20702620.2018.1463189

A comparison of diameter distribution models for<i>Khaya ivorensis</i>A.Chev. plantations in Brazil

2018· article· en· W2806018309 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSouthern Forests a Journal of Forest Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWeibull distributionMathematicsStatisticsScale (ratio)HectareBasal areaGeometryForestryGeographyCartography

Abstract

fetched live from OpenAlex

The purpose of this study was to compare Beta, Gamma, Johnson's SB and Weibull functions fitted by different methods for describing the horizontal structure of Khaya ivorensis (African mahogany) plantations in Brazil. The database comprised 128 plots from six plantations at varying ages. The function fits were compared using the Kolmogoroff–Smirnoff test, mean bias and mean absolute error for the number of trees and basal area per hectare per diameter class. Johnson's SB outperformed the other functions, although all functions provided an adequate fit. The best methods were method of moments and maximum likelihood fitted using 25% of the minimum observed diameter as the location parameter for the Johnson's SB function. The errors were greater in diameter classes with higher frequencies. Location and scale parameters were highly correlated with mean diameter and age for the Weibull and Johnson's SB functions, respectively, which is convenient for diameter prediction. Gamma's scale parameter had medium correlation with age. Beta's parameters had low correlation with stand attributes assessed.

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.

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 score0.221
Threshold uncertainty score0.721

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 studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.019
GPT teacher head0.299
Teacher spread0.280 · 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