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Record W2114085493 · doi:10.1007/978-1-4615-0031-5_1

Sources of Enteric Disease in Canada

2003· book-chapter· en· W2114085493 on OpenAlexaffabout
Tiffany T. Y. Guan, Richard A. Holley

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSalmonellaOutbreakPasteurizationCampylobacterSalmonella entericaContaminationRaw milkFood contaminantFood safetyBiologyFood microbiologyLivestockTransmission (telecommunications)Salmonella Food PoisoningFood processingEnvironmental healthBiotechnologyFood scienceMedicineBacteriaVirologyEcology

Abstract

fetched live from OpenAlex

The public is exposed to the risk of enteric infection via foodborne, waterborne, and airborne sources, or via direct contact by infected persons or animals. Food-borne transmission of enteric disease is the most well-known and extensively studied area. Among all foods, meat and poultry products are the largest contributor of foodborne disease outbreaks. Consumption of these products has been linked to enteric infection caused by several important human pathogens such as Escherichia coli O157:H7, Salmonella enterica Typhimurium, S. Enteritidis, Campylobacter species, and viruses. Food animals carry some of these human pathogens with no clinical symptoms. For example, E. coli O157:H7 carried by young cattle, Salmonella and Campylobacter by poultry. Carriage of human pathogens in food animals has serious health implications because it means the farm is a significant reservoir of foodborne illness agents. The ecology of the most frequently occurring human pathogens in the farm environment is reviewed here. Other important vehicles of foodborne gastroenteritis include fruit and vegetables, seafood, and dairy products. Fruit and vegetables, as raw agricultural commodities, are vulnerable to microbial contamination during production, and minimal processing further magnifies the contamination level. The opportunity for fresh produce contamination at production is discussed. Seafood-associated enteric infection is usually the result of environmental contamination and eating raw or undercooked seafood. The frequency of environmental contamination of seafood is examined. Enteric infection due to dairy foods often implicated raw milk, improper pasteurization, and post pasteurization contamination as sources of the problem. Some of the dairy product-associated outbreaks are addressed. Waterborne transmission is a second common route for spreading enteric disease. However when it happens, it usually results in a large number of people being affected. Drinking and recreational waters are two main vehicles. Important waterborne disease agents such as Cryptosporidium, Giardia, Shigella , and E. coli Ol57:H7 are reviewed. Airborne transmission of enteric infection is the least studied area. Airborne microbial contamination and the closely related occupational hazards are acknowledged. Some of the enteric disease agents can be spread through direct contact either by infected animals or humans themselves. Among agents spread by animal contact are verocytotoxigenic E. coli , predominantly E. coli O157:H7, Salmonella species including S. Typhimurium DT104, and Cryptosporidium . Enteric infection by personal contact has been documented for Norwalk virus, hepatitis A, Shigella species, E. coli O157:H7, and Cryptosporidium . The role of direct contact in disease transmission is addressed. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.002
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: none
Teacher disagreement score0.040
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.003

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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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

Citations0
Published2003
Admission routes2
Has abstractyes

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