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Record W2171787957 · doi:10.1139/x07-004

Graft survival and promotion of female and male strobili by topgrafting in a third-cycle slash pine (<i>Pinus elliottii</i>var.<i>elliottii</i>) breeding program

2007· article· en· W2171787957 on OpenAlexvenueno aff
Alex M. Medina Perez, Timothy L. White, Dudley A. Huber, Timothy A. Martin

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsStrobilusSlash PineBiologyPinus <genus>Crown (dentistry)BotanyHorticultureRootstockSeed orchardSowing

Abstract

fetched live from OpenAlex

A total of 2561 slash pine ( Pinus elliottii Engelm. var. elliottii) grafts were topgrafted in the winter of 2003 and evaluated in January of 2004. The objectives of this study were to understand the effect of the genetic material and crown position on survival and flowering response of topgrafts. Also, the effects of geographic direction, branch order, and scion age on topgraft response were assessed. Topgrafting was an effective tool for promoting both female and male strobili. The genetic material (scion and interstock clones) and the crown position had large effects on the promotion of female flowering and topgraft survival. More than 23% of the total variation in female flowering and 16.3% of the total variation in topgraft survival were due to differences among scion clones and among interstock clones, respectively. The highest survival rate was reached by grafting in the mid-top followed by the top crown position. Grafting in the top of the crown was highly superior in promoting female strobili followed by the mid-top position. First-order branches showed a significantly superior production of female strobili. Chronologically older scions, from selections made in the first and second generations of the tree improvement program, produced more female and male strobili than third-cycle forward selections.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.183
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.298
Teacher spread0.256 · 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 teacher head, 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

Citations14
Published2007
Admission routes1
Has abstractyes

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