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Record W2613796506

Geographic Variation in Specific Gravity Among Japanese Larch From Different Provenances

2007· article· en· W2613796506 on OpenAlexaboutno aff
Judy Loo, D. P. Fowler, Marco Schneider

Bibliographic record

VenueWood and Fiber Science (Society of Wood Science and Technology) · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsLarchSpecific gravityProvenanceLatitudeRange (aeronautics)Variation (astronomy)Elevation (ballistics)SowingForestryGeographyGeologyPhysical geographyBiologyBotanyGeodesyMathematicsMineralogyGeometryEngineeringPhysicsPaleontologyAstrophysics
DOInot available

Abstract

fetched live from OpenAlex

Genetic variation in wood specific gravity is reported for Japanese larch from twenty seed sources at age 17 years from planting in central New Brunswick, Canada. Information on native tamarack and European larch is also presented. Differences in mean specific gravity among provenances of Japanese larch (range 0.385 to 0.417) are highly significant. Specific gravity is not correlated with 12-year height, specific gravity of trees of the same provenances growing in Michigan, or with latitude, or elevation of the provenances. There is a weak but significant negative correlation between specific gravity and tree diameter at 1.3 m. Provenance x environment interaction in respect to specific gravity is high, making it difficult to identify provenances that will be superior over a wide area.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.201
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

Citations7
Published2007
Admission routes1
Has abstractyes

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