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Record W2045896036 · doi:10.1351/pac-rec-08-07-09

Glossary of terms used in ecotoxicology (IUPAC Recommendations 2009)

2009· article· en· W2045896036 on OpenAlexaff
Monica Nordberg, Douglas M. Templeton, Ole Andersen, John H. Duffus

Bibliographic record

VenuePure and Applied Chemistry · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGlossaryChemical nomenclatureEcotoxicologyChemistryEnvironmental chemistryLinguisticsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The objective of the "Glossary of Terms Used in Ecotoxicology" is to give clear definitions for those who contribute to studies relevant to ecotoxicology but are not themselves ecotoxicologists. This applies especially to chemists who need to understand the ecotoxicological literature without recourse to a multiplicity of dictionaries. The Glossary includes terms related to chemical speciation in the environment, sampling, monitoring and environmental analysis, as well as to adverse ecological effects of chemicals, ecological biomarkers, and the environmental distribution of chemicals. The dictionary consists of about 1139 terms. The authors hope that among the groups who will find this glossary helpful, in addition to chemists, are pharmacologists, toxicologists, ecotoxicologists, risk assessors, regulators, medical practitioners, and regulatory authorities. In particular, the glossary should facilitate the use of chemistry in relation to environmental risk assessment.

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)0.014
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0140.016
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0030.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1280.119

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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
GenreMethods

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

Citations591
Published2009
Admission routes1
Has abstractyes

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