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Record W2125228001 · doi:10.1079/9781845933913.0107

The role of livestock in the foodborne transmission of <i>Giardia duodenalis</i> and <i>Cryptosporidium</i> spp. to humans.

2009· book-chapter· en· W2125228001 on OpenAlexaff
Brent R. Dixon

Bibliographic record

VenueCABI eBooks · 2009
Typebook-chapter
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsHealth Canada
Fundersnot available
KeywordsCryptosporidiumLivestockGiardiaTransmission (telecommunications)OutbreakBiologyZoonosisVeterinary medicineMicrobiologyVirologyFecesEcologyMedicine

Abstract

fetched live from OpenAlex

While person-to-person and waterborne transmission probably account for most human infections with Giardia duodenalis and Cryptosporidium spp., zoonotic transmission, particularly from livestock, has generated a great deal of interest in recent years. Both G. duodenalis and Cryptosporidium spp. are highly prevalent in cattle and other livestock, and zoonotic genotypes and species of these parasites have been identified in numerous studies. There is limited evidence, however, supporting the role of livestock as reservoirs for human infection. The association of livestock with the foodborne transmission of these parasites is also poorly recognized. Nevertheless, these animals have been associated with the presence of Giardia cysts and Cryptosporidium oocysts in a variety of foods, as well as with some foodborne outbreaks. The possible role of livestock in the contamination of produce, meats and other foods with G. duodenalis and Cryptosporidium spp., and its public health significance will be discussed.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.007
GPT teacher head0.216
Teacher spread0.208 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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