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Record W2097524996 · doi:10.1002/clen.200900042

Development of French Indoor Air Quality Guidelines

2009· article· en· W2097524996 on OpenAlexaboutno aff
Corinne Mandin, Nathalie Bonvallot, Séverine Kirchner, Marion Keirsbulck, René Alary, Pierre‐André Cabanes, Frédéric Dor, Yvon Le Moullec, Jean‐Ulrich Mullot, Anne-Elisabeth Peel, Christophe Rousselle

Bibliographic record

VenueCLEAN - Soil Air Water · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Environmental healthEnvironmental epidemiologyInternational agencyAir quality indexHazardBusinessOccupational safety and healthPopulationIndoor air qualityOccupational exposure limitEnvironmental protectionEnvironmental planningEnvironmental scienceMedicineOccupational exposureGeographyEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract Indoor air quality guidelines (IAQGs) provide safe levels of indoor pollutant concentrations below which adverse health effects are not expected to occur in the general population, including susceptible subgroups. The French Agency for Environmental and Occupational Health Safety and the French Scientific and Technical Centre for Building have been leading a national working group to develop IAQGs based on health criteria. Firstly, a list of substances of concern was established for which IAQGs should be provided, and priority substances were identified. For each substance, toxicological and epidemiological data was reported and discussed. A critical effect and, if possible, a mode of action explaining the toxicity was described. Existing health based IAQGs already established and recommended by international groups or by some countries are collected, together with available toxicity reference values from the US Environmental Protection Agency, the Agency for Toxic Substances and Disease Registry, the California Office of Environmental Health Hazard Assessment, Health Canada and the Dutch Agency for Environmental Health. After an in‐depth analysis of these values, IAQGs are proposed. The production of an IAQG for a threshold pollutant (formaldehyde) and for a non‐threshold carcinogenic compound (benzene) are presented as examples.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.002

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 head0.091
GPT teacher head0.352
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

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

Citations17
Published2009
Admission routes1
Has abstractyes

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