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Molecular Interactions Between<i>Leptosphaeria maculans</i>and<i>Brassica</i>Species

2022· review· en· W4280608675 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Phytopathology · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsAgriculture and Agri-Food Canada
FundersGrains Research and Development CorporationSaskatchewan Canola Development Commission
KeywordsLeptosphaeria maculansBlacklegCanolaBiologyBrassicaGeneGeneticsBiotechnologyBotany

Abstract

fetched live from OpenAlex

Canola is an important oilseed crop, providing food, feed, and fuel around the world. However, blackleg disease, caused by the ascomycete Leptosphaeria maculans, causes significant yield losses annually. With the recent advances in genomic technologies, the understanding of the Brassica napus–L. maculans interaction has rapidly increased, with numerous Avr and R genes cloned, setting this system up as a model organism for studying plant–pathogen associations. Although the B. napus–L. maculans interaction follows Flor's gene-for-gene hypothesis for qualitative resistance, it also puts some unique spins on the interaction. This review discusses the current status of the host–pathogen interaction and highlights some of the future gaps that need addressing moving forward.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.310
Teacher spread0.271 · 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