Developing ToF‐SIMS methods for investigating the degradation of plastic debris on beaches
Bibliographic record
Abstract
Abstract Plastic debris in the Earth's oceans and larger freshwater (FW) bodies presents a serious environmental threat to aquatic organisms. Degradation of plastic by mechanical erosion and chemical weathering is minimal in water. Once deposited on beaches, plastic fragments are exposed to UV radiation and physical processes controlled by winds, currents and waves. Recent work has indicated that saltwater (SW) beach plastics feature both mechanically and chemically weathered surface textures, wherein mechanically weakened fractures are the sites of granular oxidation textures. Analysis of lacustrine (FW) beach plastics is now ongoing, and shows similar textural effects of mechanical and chemical weathering. TOF‐SIMS, with its high spatial resolution and ability to detect molecular species, is ideally suited to explore chemical changes and oxidative processes occurring in these plastics. The method enables detection of low levels of absorbed species present in oxidized polymeric materials. TOF‐SIMS analysis is currently being conducted to investigate the oxidation process in polyethylene beach plastics from both SW (Kauai, HI, USA) and FW (Lake Huron, ON, Canada) beaches. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".