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Record W6948737319 · doi:10.5061/dryad.3tx95x6qk

Partial consumption of medical face masks by a common beetle species

2024· dataset· en· W6948737319 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

VenueDRYAD · 2024
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicroplasticsForagingConsumption (sociology)BranFace masksFood consumptionFeather

Abstract

fetched live from OpenAlex

The widespread distribution of microplastics (MPs) in the environment has motivated research on the ecological significance and fate of these pervasive particles. Recent studies have demonstrated that MPs may not always have negative effects and in contrast, several species of Tenebrionidae beetles utilized plastic as a food source in controlled laboratory experiments. However, most studies of plastic-eating insects have not been ecologically realistic, and thus it is unclear whether results from these experiments apply more broadly. Here we quantified the ability of mealworms (Coleoptera: Tenebrionidae) to consume MPs derived from polypropylene (PP) and polylactic acid (PLA) face masks; these are two of the most commonly used conventional and plant-based plastics. To simulate foraging in nature, we mixed MPs with wheat bran to create an environment where beetles were exposed to multiple food types. Mealworms consumed ~50% of the MPs, egested a small fraction, and consumption did not affect survival. This study adds to our limited knowledge of the ability of insects to consume MPs. Understory or ground-dwelling insects may hold the key to sustainable plastic disposal strategies, but we caution that research in this field needs to proceed concomitantly with reductions in plastic manufacturing.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.045
Threshold uncertainty score0.992

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0550.009

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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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