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Record W2160506991 · doi:10.1126/science.1195203

Signatures of Adaptation to Obligate Biotrophy in the <i>Hyaloperonospora arabidopsidis</i> Genome

2010· article· en· W2160506991 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

VenueScience · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food Canada
FundersBiotechnology and Biological Sciences Research CouncilWellcome Trust
KeywordsObligateOomyceteBiologyGenomeBotanyGeneticsGene

Abstract

fetched live from OpenAlex

From Blight to Powdery Mildew Pathogenic effects of microbes on plants have widespread consequences. Witness, for example, the cultural upheavals driven by potato blight in the 1800s. A variety of microbial pathogens continue to afflict crop plants today, driving both loss of yield and incurring the increased costs of control mechanisms. Now, four reports analyze microbial genomes in order to understand better how plant pathogens function (see the Perspective by Dodds ). Raffaele et al. (p. 1540 ) describe how the genome of the potato blight pathogen accommodates transfer to different hosts. Spanu et al. (p. 1543 ) analyze what it takes to be an obligate biotroph in barley powdery mildew, and Baxter et al. (p. 1549 ) ask a similar question for a natural pathogen of Arabidopsis . Schirawski et al. (p. 1546 ) compared genomes of maize pathogens to identify virulence determinants. Better knowledge of what in a genome makes a pathogen efficient and deadly is likely to be useful for improving agricultural crop management and breeding.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.110

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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