Reducing the Uncertainty of Microplastic Identification and the Preferred Use of the Varnish clam (<i>Nuttallia obscurata</i>) as Compared to Other Bivalves as a Biomonitor of Plastic Pollution
Bibliographic record
Abstract
By integrating both laboratory experiments and field studies, we demonstrate the efficacy of the varnish clam ( Nuttallia obscurata ) as a bioindicator for assessing microplastic pollution. By employing three spectral libraries: (1) a commercial library associated with FTIR instrumentation, (2) spectra derived from derelict shellfish aquaculture gear (DSAG), and (3) spectra representing six polymers commonly found in marine environments and naturally aged over 6 months, we confirm the clam’s ability to serve as an effective biomonitor and also its utility in pinpointing the origin of microplastics in biological matrices. This application enabled a direct relationship between DSAG and the microplastics ingested by the clam, as compared to approaches that report numbers of microplastics recovered from biological media without tracing their source. Furthermore, the use of targeted spectral libraries enhanced the accuracy of plastic composition identification. Use of such biomonitoring tools and the refinement of spectral libraries will help in evaluating the impact of plastic pollution mitigation policies, which in turn should facilitate progress toward a sustainable circular plastic economy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".