MétaCan
Menu
Back to cohort
Record W2047140077 · doi:10.1139/x09-173

Genetic correlations between spiral grain and growth and quality traits in Picea abies

2010· article· en· W2047140077 on OpenAlexvenueno aff
Henrik R. Hallingbäck, Gunnar Jansson, Björn Hannrup

Bibliographic record

VenueCanadian Journal of Forest Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersSkogforsk
KeywordsPithPicea abiesHeritabilityBiologyGenetic correlationBotanyGenetic variationEvolutionary biologyGenetics

Abstract

fetched live from OpenAlex

In Norway spruce ( Picea abies (L.) Karst), spiral grain is a major cause of twist development in sawn timber; this problem could be addressed by breeding for reduced grain angles. This study presents estimates of genetic correlations between grain angle under bark and height and diameter growth; branch number, angle, and thickness; stem straightness; ramicorn occurrence; and pilodyn penetration using data from three progeny trials. The genetic relationship between grain angle development and radial growth was also investigated by measuring multiple annual rings (3–15) in stem sections from two clonal trials. Grain angles under the bark exhibited substantial heritability but near-zero genetic correlations with all the other traits studied. The genetic correlations between multiple ring grain angle and radial growth were also close to zero among all rings. However, radial growth exhibited positive genetic correlations with grain angles at specific distances from the pith and with radial grain angle trends, suggesting that the higher grain angles in juvenile wood extend further from the pith as a result of increased radial growth. Therefore, from a sawtimber perspective, the genetic relationship with radial growth may be unfavourable, despite the lack of genetic correlations between grain angle and radial growth at any particular annual ring.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.040
GPT teacher head0.307
Teacher spread0.267 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicForest ecology and managementFrench-language works237,207