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Record W2072974778 · doi:10.1897/ieam_2008-092.1

Thresholds of toxicological concern for endocrine active substances in the aquatic environment

2009· review· en· W2072974778 on OpenAlexaff
Melanie Gross, Klaus Daginnus, Geneviève Deviller, Watze de Wolf, Stephen Dungey, C. Galli, Anne Gourmelon, Miriam N. Jacobs, Peter Matthiessen, Christian Micheletti, Earle R. Nestmann, Manuela Pavan, Ana B. Payá-Pérez, Hans‐Toni Ratte, B. Safford, Birgit Sokull‐Klüttgen, Frauke Stock, Hans‐Christian Stolzenberg, James Wheeler, Marc Willuhn, Andrew Worth, José M. Zaldivar Comenges, Mark Crane

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2009
Typereview
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsCantox Health Sciences International
Fundersnot available
KeywordsRisk analysis (engineering)Aquatic environmentRisk assessmentHuman healthValue (mathematics)Action (physics)Aquatic toxicologyEnvironmental risk assessmentBiochemical engineeringEnvironmental scienceEnvironmental planningComputer scienceEngineeringEnvironmental healthBusinessBiologyMedicineToxicityEcologyComputer security

Abstract

fetched live from OpenAlex

The threshold of toxicological concern (TTC) concept proposes that an exposure threshold value can be derived for chemicals, below which no significant risk to human health or the environment is expected. This concept goes further than setting acceptable exposure levels for individual chemicals, because it attempts to set a de minimis value for chemicals, including those of unknown toxicity, by taking the chemical's structure or mode of action (MOA) into consideration. This study examines the use of the TTC concern concept for endocrine active substances (EAS) with an estrogenic MOA. A case study formed the basis for a workshop of regulatory, industry and academic scientists held to discuss the use of the TTC in aquatic environmental risk assessment. The feasibility and acceptability, general advantages and disadvantages, and the specific issues that need to be considered when applying the TTC concept for EAS in risk assessment were addressed. Issues surrounding the statistical approaches used to derive TTCs were also discussed. This study presents discussion points and consensus findings of the workshop.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.393
Teacher spread0.356 · 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.

Study designOther design
Domainnot available
GenreReview

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
Published2009
Admission routes1
Has abstractyes

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