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Record W3096537875 · doi:10.1093/biosci/biaa092

Towards Global Volunteer Monitoring of Odonate Abundance

2020· article· en· W3096537875 on OpenAlexaff
Jason T. Bried, Leslie Ries, Brenda D. Smith, Michael A. Patten, John C. Abbott, Joan Damerow, Robert A. Cannings, Adolfo Cordero‐Rivera, Alex Córdoba‐Aguilar, Paulo de Marco Júnior, Klaas‐Douwe B. Dijkstra, Aleš Dolný, Roy van Grunsven, D.G.H. Halstead, Filip Harabiš, Christopher Hassall, Martin Jeanmougin, Colin Jones, Leandro Juen, Vincent J. Kalkman, Gabriella J. Kietzka, Celeste Searles Mazzacano, Albert G. Orr, Mary Ann C. Perron, Maya Rocha‐Ortega, Göran Sahlén, Michael J. Samways, Adam M. Siepielski, John P. Simaika, Frank Suhling, Les G Underhill, Erin L. White

Bibliographic record

VenueBioScience · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of OttawaSaskatchewan PolytechnicMinistry of Natural Resources and ForestryRoyal British Columbia Museum
Fundersnot available
KeywordsAbundance (ecology)OdonataCitizen scienceDragonflyPerspective (graphical)EcologyPopulationGeographyEnvironmental resource managementData scienceBiologySociologyComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Insects are reportedly experiencing widespread declines, but we generally have sparse data on their abundance. Correcting this shortfall will take more effort than professional entomologists alone can manage. Volunteer nature enthusiasts can greatly help to monitor the abundance of dragonflies and damselflies (Odonata), iconic freshwater sentinels and one of the few nonpollinator insect groups appreciated by the public and amenable to citizen science. Although counting individual odonates is common in some locations, current data will not enable a global perspective on odonate abundance patterns and trends. Borrowing insight from butterfly monitoring efforts, we outline basic plans for a global volunteer network to count odonates, including organizational structure, advertising and recruiting, and data collection, submission, and synthesis. We hope our proposal serves as a catalyst for richer coordinated efforts to understand population trends of odonates and other insects in the Anthropocene.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.270
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations56
Published2020
Admission routes1
Has abstractyes

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