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Record W2020621363 · doi:10.1094/mpmi-22-12-1479

Effectors, Effectors <i>et encore des</i> Effectors: The XIV International Congress on Molecular-Plant Microbe Interactions, Quebec

2009· article· en· W2020621363 on OpenAlexaffabout
Jonathan D. Walton, Tyler J. Avis, James R. Alfano, Mark Gijzen, Pietro D. Spanu, Federico Sánchez

Bibliographic record

VenueMolecular Plant-Microbe Interactions · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsAgriculture and Agri-Food CanadaCarleton University
FundersNational Institute of Allergy and Infectious DiseasesBiotechnology and Biological Sciences Research CouncilU.S. Department of Agriculture
KeywordsEffectorLibrary scienceBiologyPolitical scienceComputer scienceImmunology

Abstract

fetched live from OpenAlex

of this journal, gave a stirring "call to action" opening address the first night.Dr. Sequeira expressed his satisfaction with the growth and quality of the scientific research presented over the years at the IS-MPMI Congresses and in the journal but reminded attendees of the need to enhance the impact and societal relevance of IS-MPMI by "translating" that research into benefits for humankind.His call for translational research became one of the recurring themes of the meeting, as other speakers responded to Dr. Sequeira's comments in their own presentations over the next four days.The importance of charitable organizations that foster translational research for agricultural development and food security, such as the Two Blades Foundation and the Bill and Melinda Gates Foundation, were mentioned by others as emerging examples of

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: none
Teacher disagreement score0.343
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0230.003

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 head0.010
GPT teacher head0.234
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2009
Admission routes2
Has abstractyes

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