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Record W3046920675 · doi:10.1201/9781003075424-9

Conclusions and Health Risk Assessment Examples

2020· book-chapter· en· W3046920675 on OpenAlexaff
D. J. Ecobichon

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsQueen's University
Fundersnot available
KeywordsRisk analysis (engineering)Computer scienceMedicine

Abstract

fetched live from OpenAlex

Risk is the probability of harm resulting from various activities or exposures and, because it is a probability, it carries numerical values between zero and one. Risk assessment conjures up the concept of a specific methodological approach, extrapolating from sets of human and animal data under conditions of relatively intense exposure and developing quantitative estimates of risk at much less intense exposures experienced by human populations. Whatever methodology that is thought to be scientifically justifiable can be used, as long as the reasons for the choices have been explicitly set forth. As J. V. Rodericks concluded, risk assessment focuses explicit recognition of the various assumptions needed to reach conclusions about risk and the uncertainties their use introduces. Human exposure can be extrapolated from extensive quantification of chemical residues in air and on surfaces as well as from transfer to, deposition on, and penetration of the skin.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0480.022

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 head0.027
GPT teacher head0.363
Teacher spread0.336 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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