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Research at Canadian zoos and botanical gardens

2005· article· en· W2064643000 on OpenAlexaffabout
William A. Rapley

Bibliographic record

VenueInternational Journal of Museum Management and Curatorship · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSocioeconomics of Resources and Conservation
Canadian institutionsToronto Zoo
Fundersnot available
KeywordsVisitor patternBotanical gardenEcologyLibrary scienceGeographyBiologyEnvironmental planningPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

Abstract Research is an important part of the work of botanical gardens and zoos in Canada, enriching their public programs and improving management of living collections. Most of these institutions participate in research activities to some extent. Approximately a half-dozen zoos and aquaria, and a similar number of botanical gardens, have large, on-going research programs and are important centres for the training of highly-qualified personnel. About half of Canadian botanical gardens and arboreta are based at universities, and many others are municipal not-for-profit organizations. In contrast, no Canadian zoos are based at universities, although several have formal links including cross-appointed staff and active graduate programs in many disciplines. A wide range of research is undertaken by, or at, these institutions that are actively involved in a broad spectrum of conservation programs, both in situ and ex situ. Projects and programs include veterinary science, husbandry or plant propagation, animal (and visitor) behaviour, ecology, habitat rehabilitation, taxonomy, systematics, physiology and phenology. Regardless of their size, these institutions make contributions to discoveries and innovations, and provide excellent collaborative opportunities for academia. Living collections also provide specimens and biological samples for a range of academic investigation, such as DNA analysis for comparative genetic purposes or reference, forensic evaluation, pathological reference, parasitology, studies in comparative anatomy or physiology, and genome banking.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.056
GPT teacher head0.278
Teacher spread0.222 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations4
Published2005
Admission routes2
Has abstractyes

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Same venueInternational Journal of Museum Management and CuratorshipSame topicSocioeconomics of Resources and ConservationFrench-language works237,207