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Record W3084828412 · doi:10.1111/ina.12722

Toward setting public health guidelines for chemicals in indoor settled dust?

2020· article· en· W3084828412 on OpenAlexaff
Philippe Glorennec, Derek G. Shendell, Pat E. Rasmussen, Roger Waeber, Peter Egeghy, Kenichi Azuma, Aurélie Pelfrêne, Barbara Le Bot, Williams Estève, Guillaume Perouel, Valérie Pernelet Joly, Y. Noack, Matthieu Delannoy, Marion Keirsbulck, Corinne Mandin

Bibliographic record

VenueIndoor Air · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth Canada
FundersU.S. Environmental Protection Agency
KeywordsGuidelineRelevance (law)Environmental healthIndoor airEnvironmental planningEnvironmental scienceHuman healthPublic healthEnvironmental protectionEnvironmental engineeringPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Indoor settled dust may result in substantial human exposure to chemicals, especially by ingestion following hand-to-mouth or hand-to-object-to-mouth contact. As with other environmental media related to exposure, dust may thus be subject to regulation. An international scientific workshop was convened in Paris in September 2019 firstly to assess the relevance for public health of setting guidelines for indoor settled dust, and secondly to discuss scientific and technical challenges related to such guidelines. The main discussions and conclusions, with consensus achieved, are reported herein. Discussions concerned general considerations, objectives and definitions, relevance for a health-based guideline, units of measure, and finally derivation of the guideline. These points should be addressed when considering an indoor settled dust guideline as part of a policy to reduce exposure indoors to a given chemical or group of chemicals.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.274
GPT teacher head0.396
Teacher spread0.121 · 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 designNot applicable
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

Citations21
Published2020
Admission routes1
Has abstractyes

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