Examining ingested microplastics in fish: Considerations on filter pore size, analysis time, and material costs to design cost-effective projects
Bibliographic record
Abstract
In recent years the microplastics research community has called for methods harmonization and standardized metrics of reporting microplastic attributes. While alignment of research practices is essential in obtaining robust microplastic data, resource managers need to balance how the cost and effort of methodologies compare to data output. The intention of this study is to compare two recommended methods for isolating anthropogenic microparticles in fish gastrointestinal tracts. Using Icelandic capelin (Mallotus villosus) as a study species, with potassium hydroxide (KOH) digestion, we compared a 1.2 μm filtration and 45 μm sieving protocols for isolating ingested anthropogenic microparticles. We compared methods based on the amount of time they took to conduct, the cost of the materials and equipment required, levels of procedural contamination, and data output. We found no significant differences in the materials costs or procedural contamination between the two methods. However, the two protocols resulted in anthropogenic microparticles with significantly different characteristics (i.e. colour, length, morphology), and the 45 μm sieving protocol took longer to conduct per sample. Our results contribute towards a more holistic understanding of microplastic research methods, their relative costs, and how they contribute to data outputs and development of large-scale monitoring programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".