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Record W4220919902 · doi:10.2903/j.efsa.2022.7124

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): antimicrobial‐resistant Brachyspira hyodysenteriae in swine

2022· article· en· W4220919902 on OpenAlexaff
Søren Saxmose Nielsen, Dominique Bicout, Paolo Calistri, Elisabetta Canali, Julian Ashley Drewe, Bruno Garin‐Bastuji, José Luis Gonzales Rojas, Christian Gortázar, Mette Herskin, Virginie Michel, Miguel Ángel Miranda Chueca, Barbara Padalino, Helen Clare Roberts, Hans Spoolder, Karl Ståhl, Antonio Velarde, Arvo Viltrop, Christoph Winckler, Francesca Baldinelli, Alessandro Broglia, Lisa Kohnle, Yves Van der Stede, Julio Álvarez

Bibliographic record

VenueEFSA Journal · 2022
Typearticle
Languageen
FieldVeterinary
TopicVeterinary medicine and infectious diseases
Canadian institutionsAlpha Technologies (Canada)
Fundersnot available
KeywordsListing (finance)AntimicrobialAnimal healthHealth claims on food labelsBiologyLawPolitical scienceMedicineMicrobiologyBusinessVeterinary medicineFood science

Abstract

fetched live from OpenAlex

Brachyspira hyodysenteriae (B. hyodysenteriae) was identified among the most relevant antimicrobial-resistant (AMR) bacteria in the EU for swine in a previous scientific opinion. Thus, it has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on its eligibility to be listed, Annex IV for its categorisation according to disease prevention and control rules as in Article 9, and Article 8 for listing animal species related to the bacterium. The assessment has been performed following a methodology previously published. The outcome is the median of the probability ranges provided by the experts, which indicates whether each criterion is fulfilled (lower bound ≥ 66%) or not (upper bound ≤ 33%), or whether there is uncertainty about fulfilment. Reasoning points are reported for criteria with uncertain outcome. According to the assessment here performed, it is uncertain whether AMR B. hyodysenteriae can be considered eligible to be listed for Union intervention according to Article 5 of the AHL (33–66% probability). According to the criteria in Annex IV, for the purpose of categorisation related to the level of prevention and control as in Article 9 of the AHL, the AHAW Panel concluded that the bacterium does not meet the criteria in Sections 1, 2 and 3 (Categories A, B and C; 1–10%, 10–33% and 10–33% probability of meeting the criteria, respectively) and the AHAW Panel was uncertain whether it meets the criteria in Sections 4 and 5 (Categories D and E, 50–90% and 33–66% probability of meeting the criteria, respectively). The main animal species to be listed for AMR B. hyodysenteriae according to Article 8 criteria are pigs and some species of birds, such as chickens and ducks.

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)0.079
metaresearch head score (Gemma)0.105
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.105
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.004
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0020.005
Research integrity0.0040.002
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 head0.028
GPT teacher head0.331
Teacher spread0.302 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2022
Admission routes1
Has abstractyes

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