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Record W2028771371 · doi:10.5558/tfc86225-2

Juvenile productivity of five hybrid poplar clones and 20 genetically improved white and Norway spruces in boreal clay-belt of Quebec, Canada

2010· article· en· W2028771371 on OpenAlexafffundvenueabout
Marie Larchevêque, Guy R. Larocque, Francine Tremblay, Stéphane Gaussiran, Robert D. Boutin, Suzanne Brais, Jean Beaulieu, Gaëtan Daoust, Pierre Périnet

Bibliographic record

VenueThe Forestry Chronicle · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsCentre Technologique des Résidus IndustrielsMinistère des Ressources naturelles et des Forêts (Québec)Natural Resources CanadaUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
FundersGovernment of Canada
KeywordsTaigaPicea abiesProductivityBiologyHybridWhite (mutation)BorealForestryBlack spruceGeographyEcologyAgronomy

Abstract

fetched live from OpenAlex

Similar to other boreal regions of Canada, northwestern Quebec has abundant lands available for the establishment of high-productivity plantations. However, few genetically improved species have been tested for this region. Three sites were planted with five hybrid poplar clones; 19 families of white spruce (Picea glauca [Moench] Voss) of southern Ontario and Quebec origins; 20 families of Norway spruce (Picea abies [L.] Karst.) of northeastern European origins; and a local seed source of white spruce. Survival and productivity were evaluated during their first three growing seasons. Survival rate was high for all selected plant material. For white spruce, genetically improved families were more productive than the local seed source. The use of exotics (Norway spruce or P. maximowiczii hybrids) did not confer any growth benefit at this early stage. Key words: survival, height, root collar diameter, field trial, exotic and native species

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)0.000
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 score0.253
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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

Citations5
Published2010
Admission routes4
Has abstractyes

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