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Record W4362585150 · doi:10.5558/tfc2023-014

Évaluation des effets de l’entaillage de l’érable à sucre sur la production de bois d’oeuvre

2023· article· fr· W4362585150 on OpenAlexaffvenue
François Guillemette, Sébastien Michaud-Larochelle, Steve Bédard, Stéphane Tremblay

Bibliographic record

VenueThe Forestry Chronicle · 2023
Typearticle
Languagefr
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsForestryArtGeography

Abstract

fetched live from OpenAlex

La demande croissante des produits confectionnés à partir de la sève d’érable amène à revoir les objectifs de production pour certains peuplements qui étaient jusqu’à présents destinés à une production prioritaire de bois d’oeuvre d’érable à sucre (Acer saccharum Marshall). Il est donc pertinent d’estimer les impacts que la production acéricole pourrait avoir sur la production de bois d’oeuvre d’érable à sucre. Nous avons d’abord mis au point un modèle permettant de prévoir la perte de bois d’oeuvre dans un érable à sucre causée par l’entaillage pour la collecte de la sève. Nous avons ensuite utilisé ce modèle pour simuler deux scénarios d’aménagement : un pour la production de bois d’oeuvre seule et un pour la coproduction de bois et de sève dans un même peuplement. Les résultats obtenus suggèrent que le volume net de bois d’oeuvre récolté d’érable à sucre est diminué d’environ 40 % dans le scénario de co-production comparativement au scenario de production de bois.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.243
Teacher spread0.221 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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