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Record W4392882070 · doi:10.1002/9781119555278.ch9

Planning, design and construction of the modern animal facility

2024· other· en· W4392882070 on OpenAlexaboutno aff
Ken Applebee, Christopher H. J. Sear, Steven Cubitt

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicAgriculture, Water, and Health
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectural engineeringEngineeringComputer scienceConstruction engineering

Abstract

fetched live from OpenAlex

The purpose and function of a research animal facility is to effectively support an institution's biomedical research goals by providing appropriate laboratory space and services, plus promoting the health and welfare of the housed animals and its staff. Legislation has become increasingly harmonised, globally, with the UK, European Union, USA, Canada and Australia influencing the wider geopolitical regulatory frameworks. Legislation impacts the design of research animal facilities through the type of approach to approval/certification/licensure of the new facility taken by the specific regulatory authority. The building management system is also often used to monitor and record the environmental conditions within specific animal housing rooms, thus providing evidence of stability and demonstrating compliance with animal welfare legislation. The design and build of a research animal facility is a complex matter, involving the co-ordination and integration of biomedical, operational, infrastructural and regulatory factors.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.090
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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