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Record W3169881122 · doi:10.22230/jem.2021v21n1a609

Disease Screening for Endangered Whitebark Pine Ecosystem Recovery

2021· article· en· W3169881122 on OpenAlexafffundabout
Michael P. Murray, Ward B. Strong

Bibliographic record

VenueJournal of Ecosystems and Management · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsMinistry of Forests
FundersNature Conservancy of CanadaU.S. Forest ServiceParks CanadaNature ConservancyAlberta Environment and Parks
KeywordsBiologySeedlingEndangered speciesEcologyAgronomyHabitat

Abstract

fetched live from OpenAlex

Whitebark pine (Pinus albicaulis) is a high-mountain keystone and foundation species that is declining throughout most of its range in Western Canada. An introduced pathogen (Cronartium ribicola) causing white pine blister rust has led to the tree being listed as a federal species at risk. A disease screening program relies on carefully selecting potentially resistant parent trees, followed by testing their respective progenies. Beginning in 2011, trees were selected for controlled inoculations and field trials of seedling families. The performance of each seedling family indicates the level of disease susceptibility, implying genetic resistance in the parents. To date, we are screening hundreds of wild-collected parents. Based on post-inoculation assessments, almost one-third of our carefully selected parents have produced seedlings showing low susceptibility to disease. Numerous stakeholders are now beginning to plant disease resistant seedlings while also supporting the establishment of seed orchards and clone banks. Due to everchanging pathosystems, long-term diseasem screening will remain a critical contribution to the recovery of this valuable species.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.368

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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 designNot applicable
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
Published2021
Admission routes3
Has abstractyes

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