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Record W2316906946 · doi:10.1139/x11-164

Effects of seedling age on blister rust resistance assessments in eastern white pine and its hybrid backcrosses

2011· article· en· W2316906946 on OpenAlexafffundvenue
Pengxin Lu, Darren Derbowka

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsOntario Forest Research Institute
FundersMinistry of Natural Resources
KeywordsSeedlingInoculationBiologyResistance (ecology)HorticultureRust (programming language)Growing seasonWhite (mutation)BotanyAgronomy

Abstract

fetched live from OpenAlex

Seedling age at the time of artificial white pine blister rust ( Cronartium ribicola J.C. Fisch.) inoculation can affect the duration and accuracy of resistance assessments for eastern white pine ( Pinus strobus L.) and its hybrid backcrosses and thereby affect advances in breeding programs intended to enhance genetic resistance to the pathogen. Based on postinoculation seedling mortality rates, up to 5 years were required to rank resistance of eastern white pine genotypes when seedlings were inoculated with C. ribicola at 2 years of age compared with less than 2 years when they were inoculated after the first growing season. In this study, we evaluated and compared consistency of genotype rankings in seedling mortality rates between the two inoculation approaches. Assessment results from inoculating seedlings after the first growing season proved as reliable as those achieved by inoculating them after the second growing season. Inoculating seedlings at a younger age not only substantially reduced experimental time and costs but also allowed a larger number of seedlings to be screened for resistance, leading to higher experimental precision.

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)0.001
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 score0.044
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.323
Teacher spread0.276 · 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

Citations4
Published2011
Admission routes3
Has abstractyes

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