MétaCan
Menu
Back to cohort
Record W7075370947

Critical reviews of exposure assessment in carcinogenic hazard identification: the IARC Monographs experience

2024· article· en· W7075370947 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.

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsPublic Health OntarioVeterans Affairs Canada
Fundersnot available
KeywordsExposure assessmentRisk assessmentHazardHazard analysisOccupational exposure
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: To summarise the rationale, workflow and recommendations for the conduct of exposure assessment critiques in key human studies evaluated for International Agency for Research on Cancer (IARC) Monographs on the Identification of Carcinogenic Hazards. METHODS: Approaches to evaluating exposure assessment quality in human cancer and mechanistic studies were reviewed according to the precepts outlined in the IARC Monographs Preamble, using two agents as case studies. Exposure assessment 'domains', that is, salient aspects of exposure assessment for the agent under evaluation, were selected for review across the key human studies. RESULTS: The case studies of night shift work (volume 124) and 1,1,1-trichloroethane (volume 130) used a common approach, tailored to the agents' specific exposure scenarios, to evaluate exposure assessment quality. Based on the experiences of IARC Working Groups to date, the implementation of exposure assessment critique requires the need for agent-specific knowledge, consideration of the validity of time-varying exposure metrics related to duration and intensity, and transparent, concise reviews that prioritise the most important strengths and limitations of exposure assessment methods used in human studies. CONCLUSIONS: Exposure assessment has not historically been a fully appreciated component for evaluating the quality of epidemiological studies in cancer hazard identification. Exposure assessment critique in key human cancer and mechanistic studies is now an integral part of IARC Monographs evaluations and its conduct will continue to evolve as new agents are evaluated. The approaches identified here should be considered as a potential framework by others when evaluating the exposure assessment component of epidemiological studies for systematic reviews.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.241
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