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Record W4285742390 · doi:10.1002/ael2.20083

Mercury accumulation in honey bees trends upward with urbanization in the USA

2022· article· en· W4285742390 on OpenAlex
Prashant Waiker, Yener Ulus, Martin Tsz‐Ki Tsui, Olav Rueppell

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

VenueAgricultural & Environmental Letters · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUrbanizationMercury (programming language)Environmental sciencePollutantWildlifeEcologyEnvironmental protectionGeographyEnvironmental chemistryBiologyChemistry

Abstract

fetched live from OpenAlex

Abstract Urbanization has profound implications for associated ecosystems and organisms. Monitoring pollutants inform risk assessments for human and wildlife health. Honey bees ( Apis mellifera ) forage widely and collect food from many sources. Thus, they may be a robust integrator of environmental pollutants. Here, we collected honey bees from 10 different locations across the United States to quantify their content of total mercury (THg) and methylmercury (MeHg). Although our limited sample size prevented a meaningful statistical evaluation, we found that bees from urbanized areas had higher THg than those from rural areas, with suburban samples intermediate. The MeHg concentrations in all samples were below the detection limit. Despite its limited scope, this first preliminary dataset on Hg levels in honey bees across the United States suggests that urbanization may play a role in increasing Hg exposure to these pollinators, and that honey bees may be a useful biomonitor of the environmental presence of chemical pollutants.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.224
Teacher spread0.202 · 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