Critical Gaps in Shoreline Plastics Pollution Research
Bibliographic record
Abstract
Shoreline surveys are an accessible and common method for monitoring plastic pollution in aquatic environments. Their results are critical to well-informed pollution mitigation efforts. Here, we show that three environmental variables: (1) coarse sediment, (2) accumulations of organic material, and (3) snow and ice are dramatically underrepresented by existing shoreline plastic pollution research efforts. We reviewed 361 published shoreline surveys, encompassing 3,284 sample sites, and found that only 4% of sites included coarse sediment, only one study described sampling organic material for plastic, and only 2.5% of sites are sampled in the presence of ice or snow. The relative absence of these environmental variables may stem from the tailoring of shoreline survey guidelines to a narrow range of shoreline environments. These three features influence plastic deposition and retention on shorelines, and their underrepresentation signals a need to recalibrate research efforts towards better methodological reporting, and regional representation and relevance.
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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 | 0.063 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".