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Record W2969848214 · doi:10.1093/njaf/24.1.22

Stand Density Management Diagram for Jack Pine Stands in Eastern Canada

2007· article· en· W2969848214 on OpenAlexaboutno aff
Mahadev Sharma, S.Y. Zhang

Bibliographic record

VenueNorthern Journal of Applied Forestry · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsThinningDiagramHectareMathematicsLimit (mathematics)Environmental scienceStatisticsForestryGeographyMathematical analysis

Abstract

fetched live from OpenAlex

Abstract A stand density management diagram was developed for jack pine (Pinus banksiana Lamb.) stands using the data obtained from 125 permanent sample plots (PSPs) established in Ontario and 232 PSPs in Quebec, Canada. The diagram was evaluated using data from 40 PSPs established in Ontario. Recently developed and efficient models have been used in constructing the diagram to estimate diameters and heights for the trees for which no diameters or heights were recorded at the time of stand inventory. Relative density indices of 0.15, 0.40, and 0.55 were used, corresponding to the line of approximate crown closure, the limit of productive zone, and the lower limit of competition-related mortality, respectively. If two stand characteristics are known, including mean total tree volume, quadratic mean diameter, trees per hectare, and average dominant height, the others can be readily obtained using the diagram. The consequences of various thinning scenarios can be plotted and visualized in the field without the need for computer simulation.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.329
Threshold uncertainty score0.662

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.202
Teacher spread0.196 · 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 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

Citations14
Published2007
Admission routes1
Has abstractyes

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