MétaCan
Menu
Back to cohort
Record W4312420073 · doi:10.32473/edis-fs130-2015

Preventing Foodborne Illness: Cyclosporiasis cayetanensis

2015· article· en· W4312420073 on OpenAlexaboutno aff
Keith R. Schneider, Rachael Silverberg, Susie Richardson, Renée M. Goodrich‐Schneider

Bibliographic record

VenueEDIS · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsCyclospora cayetanensisCyclosporaDiarrheaIncidence (geometry)VirologyMedicineEnvironmental healthBiologyFecesMicrobiologyCryptosporidiumPathology

Abstract

fetched live from OpenAlex

Cyclospora cayetanensis is a microscopic, spore-forming, intestinal protozoan parasite and a known cause of the gastrointestinal infection cyclosporiasis, often referred to as “traveler’s diarrhea” for its prevalence among visitors to regions where the species is endemic. These organisms have a protective covering that makes them resistant to disinfectants and that gives Cyclospora the ability to survive outside of hosts for extended periods. The incidence of cyclosporiasis has been increasing worldwide, with several documented cases in the United States and Canada. This revised 4-page fact sheet was written by Keith R. Schneider, Rachael Silverberg, Susie Richardson, and Renée Goodrich Schneider, and published by the UF Department of Food Science and Human Nutrition, March 2015. (Photo: CDC/DPDx – Melanie Moser) FSHN0519/FS130: Preventing Foodborne Illness: Cyclosporiasis (ufl.edu)

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.005

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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEDISSame topicParasitic Infections and DiagnosticsFrench-language works237,207