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Current and future molecular approaches to investigate the white pine blister rust pathosystem

2010· article· en· W2106046603 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueForest Pathology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsCanadian Forest Service
FundersU.S. Forest Service
KeywordsPathosystemBiologyRust (programming language)Population geneticsConservation geneticsEvolutionary biologyGeneticsPopulationMicrosatellitePathogenGene

Abstract

fetched live from OpenAlex

Summary Molecular genetics is proving to be especially useful for addressing a wide variety of research and management questions on the white pine blister rust pathosystem. White pine blister rust, caused by Cronartium ribicola , is an ideal model for studying biogeography, genetics, and evolution because: (1) it involves an introduced pathogen; (2) it includes multiple primary and alternate hosts occurring in large, relatively undisturbed ecosystems; (3) some hosts exhibit endemic resistance; and (4) the disease interaction is long enduring. Molecular techniques are used to investigate population genetics, phylogenetics, hybrids, and proteomics in white pine ( Pinus , subgenus Strobus ) and blister rust ( Cronartium ) and the genetics of resistance and virulence in the blister rust pathosystem. These techniques include genetic markers, mapping, microarrays, sequencing, association genetics, genomics, and genecology. Molecular genetics contributes to gene conservation, breeding for resistance, and ecosystem management.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.225
Teacher spread0.203 · 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