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Record W1908293491 · doi:10.1002/ieam.1545

The role of persistence in chemical evaluations

2014· article· en· W1908293491 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsEnvironment and Climate Change CanadaHealth CanadaTrent University
FundersHealth Canada
KeywordsPersistence (discontinuity)HazardHazard analysisRisk assessmentHarmRisk analysis (engineering)Computer scienceEnvironmental scienceBiochemical engineeringReliability engineeringEngineeringPsychologyBusinessBiologyEcologyComputer security

Abstract

fetched live from OpenAlex

Abstract The initial stage in the assessment and priority setting of chemicals for their potential to cause harm to humans and the environment is usually a hazard assessment employing metrics for persistence, bioaccumulation, and inherent toxicity. This hazard assessment is followed, when necessary, by the more demanding task of risk assessment. Hazard assessment of data and processes influencing persistence are discussed, leading to a number of suggestions for more effective evaluation. These include 1) an initial focus on accurate data for intensive chemical partitioning and reaction half-life properties that are universally applicable as distinct from extensive properties that can be included later on a location-specific basis; 2) separate treatments of near-field and far-field exposures; 3) a focus on persistence and its effect on levels of exposure, especially for substances for which “time to exposure” is less than “time to degradation” and have been termed “pseudo-persistent.” We show that “continuously present” is a better descriptor of this concern. Case studies illustrate and support these suggestions. Data on the intensive properties and on exposure pathways are best combined in evaluative multimedia mass balance models that can provide a clear depiction of the likely chemical fate, exposure routes, and levels. The information generated by the mass balance models can serve to justify and direct a full risk assessment that includes region-specific information on chemical quantities, estimates of exposure, and potential for adverse effects. Integr Environ Assess Manag 2014;10:588–594. © 2014 SETAC Key Points We demonstrate the importance of persistence as a criterion for hazard assessment of chemicals. We show the merit of addressing intensive chemical properties before extensive properties, We show the need to address near-field and far-field exposures separately. We introduce the concept of "time to exposure" and use it to show that continuously present is a term preferable to pseudo-persistent. These key points are illustrated using hypothetical case studies involving simple mass balance calculations.

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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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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