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Record W2282660947 · doi:10.22038/apjmt.2015.6358

Asian Implications of Aflatoxin and Dioxin Foodborne Chemical Exposures Based on World Health Organization Estimates

2015· article· en· W2282660947 on OpenAlexaff
Herman J. Gibb, Brecht Devleesschauwer, P. Michael Bolger, Felicia Wu, Janine Ezendam, Julie Cliff, Marco J. Zeilmaker, P Verger, John I. Pitt, Janis Baines, G. O. Adegoke, Reza Afshari, Yan Liu, Bas Bokkers, Henk Van Loveren, Marcel Mengelers, Esther Brandon, Arie H. Havelaar, David C. Bellinger

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsBC Centre for Disease Control
Fundersnot available
KeywordsMedicineEnvironmental healthAflatoxinEpidemiologyDiseaseTask forceDiarrheaBiotechnologyPathology

Abstract

fetched live from OpenAlex

All people need food. Unsafe foods; however, may cause diseases ranging from diarrhea to cancer. Chemicals in food are a worldwide health concern. In 2006, the World Health Organization (WHO) organized a consultation on the global burden of foodborne diseases. Work to estimate this burden began in 2007 and was carried out by the WHO Foodborne Disease Burden Epidemiology Reference Group (FERG), which included a Chemical and Toxins Disease Task Force. The results of 8 years of work were released in December 2015.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.024
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.247
GPT teacher head0.556
Teacher spread0.309 · 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
Published2015
Admission routes1
Has abstractyes

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