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Record W2409706137 · doi:10.1017/cbo9780511805998

Environmental Toxicology

2002· book· en· W2409706137 on OpenAlexaff
David Wright, Pamela M. Welbourn

Bibliographic record

VenueCambridge University Press eBooks · 2002
Typebook
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsQueen's University
Fundersnot available
KeywordsEnvironmental toxicologyEnvironmental risk assessmentEngineering ethicsReading (process)EcologyEnvironmental planningManagement scienceToxicologyComputer scienceEngineeringRisk assessmentEnvironmental scienceBiologyChemistryPolitical science

Abstract

fetched live from OpenAlex

Environmental Toxicology is a comprehensive introductory textbook dealing with most aspects of the subject, from the molecular to the ecosystem level. Early chapters deal with basic and advanced concepts, methods and approaches. The next tier discusses the environmental toxicology of individual or groups of substances. The third part addresses complex issues, in which many of the concepts, approaches and substances covered in earlier tiers are incorporated. The fourth part includes chapters on risk assessment, rehabilitation and regulatory toxicology. The book concludes with a summary of present and future areas of emphasis. Each chapter contains a comprehensive list of references and further reading, case studies from different jurisdictions, and student exercises. Environmental Toxicology is primarily a textbook for undergraduate and graduate students in environmental toxicology, environmental chemistry, ecotoxicology, applied ecology, environmental management, and risk assessment. It will also be valuable for specialists in ecology, environmental science, and chemistry.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.160
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1600.115

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 head0.146
Teacher spread0.139 · 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

Citations192
Published2002
Admission routes1
Has abstractyes

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