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Record W3135490314 · doi:10.1093/biosci/biaa150

Ready, Set, Go: Community Science Field Campaign Reveals Habitat Preferences of Nonnative Asian Earthworms in an Urban Landscape

2020· article· en· W3135490314 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioScience · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsConcordia University
Fundersnot available
KeywordsLawnAbundance (ecology)HabitatGeographyEcologyUrban ecosystemRange (aeronautics)Urban ecologyGrasslandUrbanizationBiology

Abstract

fetched live from OpenAlex

Abstract Asian pheretimoid earthworms of the genera Amynthas and Metaphire (jumping worms) are leading a new wave of coinvasion into Northeastern and Midwestern states, with potential consequences for native organisms and ecosystem processes. However, little is known about their distribution, abundance, and habitat preferences in urban landscapes—areas that will likely influence their range expansion via human-driven spread. We led a participatory field campaign to assess jumping worm distribution and abundance in Madison, Wisconsin, in the United States. By compressing 250 person-hours of sampling effort into a single day, we quantified the presence and abundance of three jumping worm species across different land-cover types (forest, grassland, open space, and residential lawns and gardens), finding that urban green spaces differed in invasibility. We show that community science can be powerful for researching invasive species while engaging the public in conservation. This approach was particularly effective in the present study, where broad spatial sampling was required within a short temporal window.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.075
GPT teacher head0.294
Teacher spread0.219 · 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