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Record W2025175618 · doi:10.1051/jp4:20030268

Assessing risks associated with the presence of mercury in the environment: The COMERN approach

2003· article· en· W2025175618 on OpenAlex
D. Bérubé, Marc Lucotte, René Canuel

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal de Physique IV (Proceedings) · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMercury (programming language)Vulnerability (computing)Mercury contaminationEcosystemEnvironmental resource managementEnvironmental scienceEnvironmental planningComputer scienceContaminationEcologyComputer security

Abstract

fetched live from OpenAlex

The presence of mercury (Hg) in the environment has become a source of great concern in the scientific community throughout the World. However, existing models describing Hg behavior in the environment and risks to communities health attributable to Hg exposure fail to cope with the complexity of this issue. We propose a new modeling approach named the Mercury Environmental Vulnerability Index (MEVI) that takes into account notions such as ecosystems sensitivity and resilience, threshold levels of environmental effects, dynamic changes to the environment induced by human activities, and communities exposure and vulnerability to contaminants. The development of MEVI will be accomplished through the activities of a wide Canadian-based research network, the Collaborative Mercury Research Network (COMERN), during the course of its five-years research plan.

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)0.002
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 score0.112
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.281
Teacher spread0.241 · 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