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Record W4315698409 · doi:10.1017/s096272860002830x

Progress in the Reduction, Refinement and Replacement of Animal Experimentation Proceedings of the 3rd World Congress on Alternatives and Animal Use in the Life Sciences, held in Bologna, Italy, from 29 August to 2 September 1999. Edited by M Balls, A-M van Zeller and M E Halder (2000). Published by Elsevier Science BV. Obtainable from Elsevier Science BV, P O Box 211,1000 AE Amsterdam, The Netherlands, or in the USA/Canada from Elsevier Science Inc, P O Box 945, Madison Square Station, New York, NY 10160-0757, USA. Two-volume set: Developments in Animal and Veterinary Science, volumes 31A and 31B. 1858pp. Hardback (ISBN 0 444 50529 6). Price €292.69/$337.50.

2002· article· en· W4315698409 on OpenAlexaboutno aff
W. M. S. Russell

Bibliographic record

VenueAnimal Welfare · 2002
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsnot available
Fundersnot available
KeywordsResearch councilLibrary scienceBiological sciencesAnimal welfareEnvironmental ethicsBiologyPhilosophyBiotechnologyComputer science

Abstract

fetched live from OpenAlex

Progress in the Reduction, Refinement and Replacement of Animal Experimentation Proceedings of the 3rd World Congress on Alternatives and Animal Use in the Life Sciences, held in Bologna, Italy, from 29 August to 2 September 1999. Edited by M Balls, A-M van Zeller and M E Halder (2000). Published by Elsevier Science BV. Obtainable from Elsevier Science BV, P O Box 211,1000 AE Amsterdam, The Netherlands, or in the USA/Canada from Elsevier Science Inc, P O Box 945, Madison Square Station, New York, NY 10160-0757, USA. Two-volume set: Developments in Animal and Veterinary Science, volumes 31A and 31B. 1858pp. Hardback (ISBN 0 444 50529 6). Price €292.69/$337.50. - Volume 11 Issue 2

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)0.055
metaresearch head score (Gemma)0.032
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: Commentary · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0010.006
Scholarly communication0.0060.005
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.006

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 head0.055
GPT teacher head0.319
Teacher spread0.264 · 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
GenreCommentary

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
Published2002
Admission routes1
Has abstractyes

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