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Record W4313269618 · doi:10.5281/zenodo.7491180

Ekspresowa Analiza Zagrożenia Agrofagiem: Fusarium foetens Schroers, O'Donnell, Baayen & Hooftman

2018· report· en· W4313269618 on OpenAlexaboutno aff
Katarzyna Sadowska, Katarzyna Pieczul, Jakub Danielewicz, Magdalena Gawlak, Agata Olejniczak, Tomasz Kałuski

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typereport
Languageen
FieldSocial Sciences
TopicAgricultural economics and policies
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

Fusarium foetens is a new pathogen, detected in 2000 in the Netherlands, which is a leader in begonia exports to EU countries. The agrophage infects some varieties of Begonia x hiemalis (a hybrid of B. elatior). Yield losses of potted plants can reach up to 100%. To date, the pathogen has been detected several times in greenhouse and hydroponic crops in the US, Canada, Japan and, among others, in Germany, France, Norway and recently the Czech Republic. Transport of infected seedlings is the most likely way for the agrophage to spread. Phytosanitary measures, especially disinfection of greenhouse drainage water, have helped reduce the number of infections. Infected material should be withdrawn and destroyed, in order to prevent the spread of the agrophage.

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)0.001
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.102
GPT teacher head0.319
Teacher spread0.216 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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