A protocol to address the study of microplastic intake in stranded cetaceans v1
Bibliographic record
Abstract
Marine debris can impact biodiversity in a number of ways, and its effects may vary depending on the type and size of the debris and the organisms that encounter it [1]. Since the first evidence of a marine mammal's interaction with plastic intake, there have been a number of studies on this subject, together with alarming images of stomachs full of marine debris and a growing concern about it. However, very little is known about the presence of microplastics in higher trophic level species such as cetaceans [2]. Up to more recently, they were primarly focused on the study of particles larger than 2.5 cm, and therefore failing to assess the microlitter presence, which remains a challenging task due to large gut content volumes and the difficulties of sampling following careful airborne contamination prevention protocols. Working with stranded cetaceans (n=12), which represent a significant opportunity to study the interaction of marine fauna with plastic debris, we have validated a protocol for microplastic ingestion studies that serves to obtain samples from different multidisciplinary teams (i.e. veterinary and marine sciences schools), without interfering in the work of any of the parties. The successful table set up used for the extraction of microplastic particles from the gastrointestinal contents was proofed advantageous and applicable by any research group that already counts with the necessary facilities to perform cetaceans autopsy analysis, fulfilling the harmonisation needs as explicated by Panti et al. [3]. This approach is fully compatible with necropsy protocol in cetaceans [4], and at the same time complies with the recommendations for reporting ingested plastics in marine megafauna [5]. The proposed workflow allows the collection of valuable data for different interdisciplinary research teams, aiming to harmonize data, facilitate large-scale comparisons of plastic ingestion and also give scientific basis to future conservation policies. References: 1. Secretariat of the Convention on Biological Diversity and the Scientific and Technical Advisory Panel - GEF. Impacts of marine debris on biodiversity: current status and potential solutions. Montreal; 2012. Available: http://www.deslibris.ca/ID/242832 2. Moore RC, Loseto L, Noel M, Etemadifar A, Brewster JD, MacPhee S, et al. Microplastics in beluga whales (Delphinapterus leucas) from the Eastern Beaufort Sea. Mar Pollut Bull. 2020;150: 110723. doi:10.1016/j.marpolbul.2019.110723 3. Panti C, Baini M, Lusher A, Hernandez-Milan G, Bravo Rebolledo EL, Unger B, et al. Marine litter: One of the major threats for marine mammals. Outcomes from the European Cetacean Society workshop. Environ Pollut. 2019;247: 72–79. doi:10.1016/j.envpol.2019.01.029 4. Kuiken T, García-Hartmann M, editors. Cetacean pathology: dissection techniques and tissue sampling. 1993. Available: https://www.researchgate.net/publication/285819905_Cetacean_Dissection_techniques_and_tissue_sampling 5. Provencher JF, Bond AL, Avery-Gomm S, Borrelle SB, Rebolledo ELB, Hammer S, et al. Quantifying ingested debris in marine megafauna: a review and recommendations for standardization. Anal Methods. 2017;9: 1454–1469. doi:10.1039/C6AY02419J
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.132 | 0.044 |
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".