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Record W2519457259 · doi:10.1111/nrm.12105

FAUSTMANN'S FORMULAS FOR FORESTS

2016· article· en· W2519457259 on OpenAlexafffund
Robert D. Cairns

Bibliographic record

VenueNatural Resource Modeling · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec-Société et Culture
KeywordsAsset (computer security)Investment (military)Natural capitalCapital (architecture)Conjunction (astronomy)Natural resource economicsResource (disambiguation)BusinessEconomicsEnvironmental resource managementEcologyEcosystem servicesComputer scienceEcosystemGeography

Abstract

fetched live from OpenAlex

Abstract The canonical, Faustmannian forest is revisited to sharpen understanding of forests as forms of irreversibly invested capital. Investment and two r‐percent rules are discussed and re‐interpreted. A forest's two natural resources, the stand and the land, act in conjunction as a composite, sunk asset. All returns are attributed to the composite. Nonmarketed or intangible capital is also absorbed into the composite. If capital is comprehensively defined, there is no independent role for the concept of an internal rate of return. A forest provides real options in optimal and suboptimal rotation patterns. Old growth has superficial similarities to an exhaustible resource, but the forest still consists of two resources that, in conjunction, behave comparably to a plantation forest. Nonconvexities inherent in the benefits and costs of forest use indicate that implementing a sustainable program may be very difficult.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.006
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.110
GPT teacher head0.233
Teacher spread0.124 · 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 designTheoretical or conceptual
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

Citations9
Published2016
Admission routes2
Has abstractyes

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