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Record W2005260305 · doi:10.1139/x02-001

The marginal cost of structural diversity of mixed uneven-aged hard maple forests

2002· article· en· W2005260305 on OpenAlexvenueaboutno aff

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
FundersLuonnontieteiden ja Tekniikan Tutkimuksen Toimikunta
KeywordsMapleDiversity indexMathematicsStatisticsEconometricsDiversity (politics)Elasticity (physics)EcologyBiologyPhysicsSpecies richnessThermodynamics

Abstract

fetched live from OpenAlex

Theoretical concepts pertaining to the marginal cost (MC) of the structural diversity of a forest stand are developed. A matrix growth model is estimated for mixed uneven-aged forest stands of hard maple (Acer saccharum Marsh.) from southern Ontario. The estimated growth model is used to derive the MC equations for the Shannon and the Simpson indices of total structural diversity (TSD), species diversity (SD), and tree-size diversity (TD). The effects of exclusion and inclusion of the opportunity cost (OC) on the MC of the TSD are compared. The contributions of SD and TD to the MC of the TSD are disaggregated. The MCs of TSD, SD, and TD for the Shannon and the Simpson indices are iso-elastic. The elasticity of the MC of the TSD for the inclusion of OC is greater than the elasticity of MC of the TSD for the exclusion of OC. The elasticities of MC of TSD, SD, and TD for the Shannon index are greater than the elasticities of MC of TSD, SD, and TD, respectively, for the Simpson index. The elasticities of MC of SD are smaller than the elasticities of MC of TD, for both indices. However, these results are specific to the hard maple forests of southern Ontario and cannot be generalized. Some general features of MC equations of structural diversity are discussed.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.213
GPT teacher head0.261
Teacher spread0.049 · 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

Citations24
Published2002
Admission routes2
Has abstractyes

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