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Record W3125903629

Case study Guatemalan raspberries and cyclospora

2003· preprint· en· W3125903629 on OpenAlexaboutno aff
Linda Calvin, Luis Flores, William Foster

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsnot available
Fundersnot available
KeywordsCyclosporaOutbreakGeographyEnvironmental healthPublicityFood safetyDisease controlBlowing a raspberryMedicineBusinessVirologyBiologyEcologyHorticulture
DOInot available

Abstract

fetched live from OpenAlex

"The Guatemalan raspberry industry began exporting to the United States in the late 1980s, filling a market niche in the spring and fall when supplies were low. By 1996, Guatemalan raspberry exports were increasing rapidly, up 113 percent from the previous season. That spring and early summer, the U.S. Centers for Disease Control and Prevention (CDC) and Health Canada received reports of more than 1,465 cases of food-borne illness from Cyclospora, a protozoan parasite. Although no one died, the large number of cases generated substantial adverse publicity. Initially, investigators linked the outbreak to California strawberries, but they finally decided that it was associated with Guatemalan raspberries. This case study reviews the efforts to resolve this food safety problem. It is a cautionary tale about the serious impact a food safety outbreak can have on a promising industry. " from Text

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.322
Teacher spread0.251 · 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 teacher head, 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
Published2003
Admission routes1
Has abstractyes

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