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Record W2518197116 · doi:10.2903/sp.efsa.2015.en-724

Review of the state of the art of human biomonitoring for chemical substances and its application to human exposure assessment for food safety

2015· article· en· W2518197116 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEFSA Supporting Publications · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
FundersInstituto de Salud Carlos IIIInstitut de Veille SanitaireIstituto Superiore di SanitàInstitut National de la Santé et de la Recherche MédicaleHealth CanadaEuropean Food Safety Authority
KeywordsBiomonitoringEnvironmental scienceEnvironmental chemistryEnvironmental healthChemistryMedicine

Abstract

fetched live from OpenAlex

Human biomonitoring (HBM) measures the levels of substances in body fluids and tissues. Many countries have conducted HBM studies, yet little is known about its application towards chemical risk assessment, particularly in relation to food safety. Therefore a literature search was performed in several databases and conference proceedings for 2002 – 2014. Definitions of HBM and biomarkers, HBM techniques and requirements, and the possible application to the different steps of risk assessment were described. The usefulness of HBM for exposure assessment of chemical substances from food source, and for the implementation of a systematic Post Market Monitoring (PMM) approach for regulated chemical substances was evaluated. An inventory of HBM programmes provides detailed information about study design, analytical methods, reference values (RV) and biomarkers used. Environmental monitoring and associations between HBM values and food, as well as coverage of substances and remaining deficits are highlighted. The review of study results provides information on emerging chemicals, higher exposed and particularly vulnerable populations. Conclusions: HBM can bring added value for chemical risk assessment in food safety areas (namely exposure assessment), and for the implementation of a systematic PMM approach. But further work needs to be done to improve usability. Major deficits are the lack of HBM guidance values on a considerable number of substance groups, for which health based guidance values (HBGVs) have been developed, insufficient knowledge regarding exposure sources, and incomplete dietary intake assessment. Recommendations: We recommend to foster development of HBM based guidance values and validated analytical methods/BMs, stronger inclusion of substances of interest for EFSA in European surveys, expanded monitoring of highly exposed and vulnerable subgroups, uptake of EFSA guidance concerning dietary intake assessment, as well as biobanking, surveillance synergies and targeted research, and an EU wide collaborative approach to support the future use of HBM in PMM.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.265

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 science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.364
Teacher spread0.317 · 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