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Record W4409069765 · doi:10.1080/10496505.2025.2467731

A Review of CABI Digital Tools for Plant Health and Pest Risk Management

2024· review· en· W4409069765 on OpenAlexfundno aff
Hideo Ishii-Adajar, Katherine Cameron, Claire Curry, A. Li, Mariam Kadzamira, S. D. Fleming, Manju Thakur, Adewale Ogunmodede

Bibliographic record

VenueJournal of Agricultural & Food Information · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersMinistry of Agriculture of the People's Republic of ChinaAgriculture and Agri-Food CanadaCAB International
KeywordsIntegrated pest managementPEST analysisGeographyBusinessAgroforestryBiologyAgronomyMarketing

Abstract

fetched live from OpenAlex

The contribution of CABI digital tools in enhancing plant health and pest risk management is examined. Six key digital tools are reviewed to draw themes on their benefits and challenges to users and assessed using the Principles for Digital Development as a guiding framework. CABI digital tools provide quick access to relevant information, support informed decision-making, and are open access and scalable. Enhancing user accessibility and considering diverse local contexts, especially in remote areas with poor internet connectivity, can extend their impact. Addressing financial and social sustainability, including gender barriers to mobile ownership, can also increase their contribution.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.062
GPT teacher head0.309
Teacher spread0.247 · 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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

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