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Record W2174885681 · doi:10.1603/029.102.0115

A Protocol for Evaluating Cost-Effectiveness of Butterflies in Live Exhibits

2009· article· en· W2174885681 on OpenAlexaff
Adrienne L. E. Brewster, Gard W. Otis

Bibliographic record

VenueJournal of Economic Entomology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
FundersNational Science Council
KeywordsButterflyBiologyLife spanProtocol (science)Total costEcologyStatisticsToxicologyMathematicsMicroeconomicsEvolutionary biologyEconomics

Abstract

fetched live from OpenAlex

Butterfly species used for live exhibition differ in life span, encounter rate, behavior, and cost. By knowing which species are more cost-effective, exhibitors can customize their butterfly imports and purchase butterfly species that provide the best return on their investment. We used mark-recapture techniques to estimate mean life span and encounter rates for 39 butterfly species commonly purchased by exhibitors. In addition, the behavior of 29 species was quantified and characterized as suitable versus unsuitable by direct observation. The data were combined to calculate 1) the total number of days of suitable performance to be expected from a species, and 2) the cost per individual per day based on the number of expected suitable days. The most cost-effective butterfly relative to others in this study was Heliconius hecale F. (total suitable days, 33.4; cost per day, $0.05); the least cost-effective species was Doleschallia bisaltide Cramer (total suitable days, 0.1; cost per day, $13.15). By using this protocol, exhibitors can selectively incorporate more cost-effective species, save money on imports, and improve the visual appeal of their live exhibits.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.106

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 head0.162
GPT teacher head0.369
Teacher spread0.207 · 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 designObservational
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
Published2009
Admission routes1
Has abstractyes

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