High microplastic and anthropogenic particle contamination in the gastrointestinal tracts of tiger sharks (Galeocerdo cuvier) caught in the western North Atlantic Ocean
Bibliographic record
Abstract
) before quantifying and categorizing suspected anthropogenic particles (>45 μm) by size, morphology, and colour. Anthropogenic particles were found in the stomachs and spiral valve of all sharks. A total of 3151 anthropogenic particles were observed across all stomachs with 1603 anthropogenic particles observed in a single specimen. A subset of suspected anthropogenic particles (14%) were chemically identified using Raman spectroscopy and μ-Fourier Transform Infrared spectroscopy to confirm anthropogenic origin. Overall, ≥95% of particles analyzed via spectroscopy were confirmed anthropogenic, with 45% confirmed as microplastics. Of the microplastics, polypropylene (32%) was the most common polymer. Diverse microparticle morphologies were found, with fragments (57%) and fibers (41%) most frequently observed. The high occurrence and abundance of anthropogenic particle contamination in tiger sharks is likely due to their generalist feeding strategy and high trophic position compared to other marine species. The literature review resulted in 32 studies published through 2022. Several methodologies were employed, and varying amounts of contamination were reported, but none reported contamination as high as detected in our study. Anthropogenic particle ingestion studies should continue in the tiger shark, in addition to other elasmobranch species, to further understand the effects of anthropogenic activities and associated pollution on these predators.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".