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Record W3092552400 · doi:10.1016/j.fgb.2020.103476

Fungi, fungicide discovery and global food security

2020· article· en· W3092552400 on OpenAlex
Gero Steinberg, Sarah J. Gurr

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFungal Genetics and Biology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesCanadian Institute for Advanced ResearchUniversity of ExeterBill and Melinda Gates Foundation
KeywordsFungicideBiologyFood securityPopulationBiotechnologyCommodityAgricultureBusinessEcologyAgronomyEnvironmental health

Abstract

fetched live from OpenAlex

Securing sufficient food for a growing world population is of paramount importance for social stability and the well-being of mankind. Recently, it has become evident that fungal pathogens pose the greatest biotic challenge to our calorie crops. Moreover, the loss of commodity crops to fungal disease destabilises the economies of developing nations, thereby increasing the dimension of the threat. Our best weapon to control these pathogens is fungicides, but increasing resistance puts us in an arms race against them. New anti-fungal compounds need to be discovered, such as mono-alky lipophilic cations (MALCs) described herein. Collaborations between academia and industry are imperative to establish new and efficient ways to develop these new fungicides and to bring them to the market-place.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.708

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 head0.017
GPT teacher head0.239
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