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Record W3205247311 · doi:10.3390/insects12100921

“What’s This Bug?” Questions from the Public Provide Relevant Information on Species Distribution and Human–Insect Interactions

2021· article· en· W3205247311 on OpenAlexaffabout
André‐Philippe Drapeau Picard, Marjolaine Giroux, Michel Saint‐Germain, Maxim Larrivée

Bibliographic record

VenueInsects · 2021
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsEspace pour la vie
Fundersnot available
KeywordsBiologyInsectDistribution (mathematics)Evolutionary biologyEcology

Abstract

fetched live from OpenAlex

In general, insects and arthropods polarizing: they either fascinate people, disgust people, or both, and they generate lots of questions. Museums are perceived as reliable sources of information and, as such, a go-to destination for the public to receive answers. Since its opening in 1990, the Montreal Insectarium has offered an entomological information service, allowing the public to send questions, photographs, and specimens for identification. All requests are answered by entomologists. Spatiotemporal variations in taxonomic, geographic, and thematic profiles of the 4163 requests received in 2010–2011 and 2017–2018 were analyzed. Requests came from 35 countries, and most of those requests came from Canada. The majority of requests were identification requests. Representing 25% of identification requests, the five most frequent species were the eastern dobsonfly Corydalus cornutus, the masked hunter Reduvius personatus, the giant water bug Lethocerus americanus, the western conifer-seed bug Leptoglossus occidentalis, and the Japanese beetle Popillia japonica. A comparison with the data from the citizen science platform iNaturalist shows that the EIS can be a valuable tool for invasive species detection. Frequent subjects included school projects, entomophagy (eating insects), and wasp and bee nests. Finally, we discuss the role of entomologists in providing scientific information but also in addressing common concerns regarding cohabitation with arthropods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.311
Teacher spread0.252 · 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
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

Citations1
Published2021
Admission routes2
Has abstractyes

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