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Record W2903080432 · doi:10.1093/wjaf/15.2.75

Kozak's Variable-Exponent Taper Equation Regionalized for White Spruce in Alberta

2000· article· en· W2903080432 on OpenAlex
Shongming Huang, Daryl Price, Dave Morgan, Karl Peck

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWestern Journal of Applied Forestry · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsAlberta Environment and Protected Areas
Fundersnot available
KeywordsEcoregionMathematicsStatisticsExponentNon-linear least squaresTree (set theory)Explained sum of squaresMathematical analysisEcology

Abstract

fetched live from OpenAlex

Abstract Kozak's (1988) variable-exponent taper equation was estimated for white spruce by ecoregion of Alberta to reflect stem form variability among different ecoregions. Inspection of fit statistics and residual plots showed that the taper equation fitted the data quite well. Since the relative height constraint p had little impact on the overall performance of the taper equation, the optimum p value was estimated as a part of the nonlinear least squares procedures. Regional differences of the taper equation were examined and tested using the nonlinear extra sum of squares method. Ecoregions of similar taper relationships were combined to provide a composite equation. Performance of the taper equation in predicting diameter inside bark, total volume, and merchantable height was evaluated. Results indicated that the biases in predictions were small, both across different parts of the stem and for various tree sizes. West. J. Appl. For. 15(2):75-85.

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)0.000
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 score0.413
Threshold uncertainty score0.998

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)0.0030.000

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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