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Record W3046326393 · doi:10.3390/agronomy10081126

Biocontrol of Crown Gall by Rhizobium rhizogenes: Challenges in Biopesticide Commercialisation

2020· article· en· W3046326393 on OpenAlexaboutno aff
A. Kerr, G A Bullard

Bibliographic record

VenueAgronomy · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCocoa and Sweet Potato Agronomy
Canadian institutionsnot available
Fundersnot available
KeywordsBiopesticideGallBiological pest controlCrown (dentistry)BiologyNatural enemiesBiotechnologyAgroforestryGeographyBotanyAgronomyPesticideMedicine

Abstract

fetched live from OpenAlex

The biocontrol of crown gall has been practised in Australia for 48 years. Control is so efficient that it is difficult to find a galled stone fruit tree, when previously, crown gall had been a major problem. This paper explains how it works and why only pathogens are inhibited. A commercial biopesticide is available in Australia, Canada, Chile, New Zealand, Turkey, the USA, South Africa and Japan. The challenges of commercialising a biopesticide are outlined. Rigid regulations are preventing the wider use of biocontrol organisms.

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)0.003
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.214
Teacher spread0.160 · 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
GenreReview

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

Citations39
Published2020
Admission routes1
Has abstractyes

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