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Record W2551984633 · doi:10.1002/ieam.1866

Uncertainties in biological responses that influence hazard and risk approaches to the regulation of endocrine active substances

2016· article· en· W2551984633 on OpenAlexaff
Joanne L. Parrott, Poul Bjerregaard, Kristin E. Brugger, L. Earl Gray, Taisen Iguchi, Sarah M. Kadlec, Lennart Weltje, James R. Wheeler

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsEndocrine systemHazardRisk analysis (engineering)Environmental scienceRisk assessmentHazard analysisEnvironmental healthBusinessComputer scienceMedicineBiologyEngineeringInternal medicineReliability engineeringHormoneEcologyComputer security

Abstract

fetched live from OpenAlex

Abstract Endocrine-disrupting substances (EDS) may have certain biological effects including delayed effects, multigenerational effects, and may display nonmonotonic dose–response (NMDR) relationships that require careful consideration when determining environmental hazards. Endocrine disrupting substances can have specific and profound effects when exposure occurs during sensitive windows of the life cycle (development, reproduction). This creates the potential for delayed effects that manifest when exposure has ceased, possibly in a different life stage. This potential underscores the need for testing in appropriate (sensitive) life stages and full life cycle designs. Such tests are available in the Organisation for Economic Co-operation and Development (OECD) tool box and should be used to derive endpoints that can be considered protective of all life stages. Similarly, the potential for effects to be manifest in subsequent generations (multigenerational effects) has also been raised as a potential issue in the derivation of appropriate endpoints for EDS. However, multigenerational studies showing increasing sensitivity of successive generations are uncommon. Indeed this is reflected in the design of new higher tier tests to assess endocrine active substances (EAS) that move to extended one-generation designs and away from multi-generational studies. The occurrence of NMDRs is also considered a limiting factor for reliable risk assessment of EDS. Evidence to date indicates NMDRs are more prevalent in in vitro and mechanistic data, not often translating to adverse apical endpoints that would be used in risk assessment. A series of steps to evaluate NMDRs in the context of endocrine hazard and risk assessment procedures is presented. If careful consideration of delayed, multigenerational effects and NMDRs is made, it is feasible to assess environmental endocrine hazards and derive robust apical endpoints for risk assessment procedures ensuring a high level of environmental protection. Integr Environ Assess Manag 2017;13:293–301. © 2016 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC) Key Points Endocrine-disrupting substances may have certain biological effects that require careful consideration when determining environmental hazards. Delayed and multigenerational effects underscore the need for testing in appropriate, sensitive life stages and full life cycle test designs. Nonmonotonic dose–responses should be evaluated for repeatability and plausibility and any impact on the reliability of thresholds needs to be considered. If any delayed and multigenerational effects and non monotonic dose–response relationships are addressed, it is scientifically feasible to assess environmental endocrine hazards and derive robust apical endpoints for risk assessment procedures, ensuring a high level of environmental protection.

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)0.044
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.068
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0010.004
Scholarly communication0.0070.003
Open science0.0030.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.294
Teacher spread0.264 · 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 designTheoretical or conceptual
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

Citations26
Published2016
Admission routes1
Has abstractyes

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