The Toxicity of Microplastics Explorer (ToMEx) 2.0
Bibliographic record
Abstract
In 2021 the Toxicity of Microplastics Explorer (ToMEx, https://microplastics.sccwrp.org) was released as an open source, open access database and web application for microplastics toxicity. Since then, it has been utilized by the microplastic research community for the exploration, visualization, and analysis of toxicity data for both hazard characterization and risk assessment. The peer-reviewed literature has continued to grow exponentially, making ToMEx out-of-date. To ensure the continued utility of ToMEx, an international crowd-sourcing approach was utilized to update ToMEx by extracting data from additional studies published since the original release. Through this process, both the aquatic and human health ToMEx databases roughly doubled in size, and modest increases in data diversity (e.g., number of species represented, types of test particles) were observed in the aquatic organisms database. However, most trends (e.g., greater toxicities observed with smaller particle sizes, lack of dose-response data etc.) observed in the first iteration of ToMEx remained constant. A previously developed framework for deriving ecological health-based microplastic thresholds using species sensitivity distributions was reapplied to determine how thresholds and their associated uncertainty intervals would change following the database update. Twelve new studies passed minimum screening criteria and were deemed fit for the purpose of threshold derivation. The addition of new data allowed for the separation of freshwater and marine compartments which had previously been combined due to a lack of applicable toxicity data for freshwater species. When molecular and cellular level endpoints were included, freshwater thresholds were comparable or increased from values calculated using previous data (-5 to 2.5-fold change) whereas marine thresholds dramatically decreased (-5000 to -29-fold change). However, when endpoints were restricted to organism and above, marine and freshwater thresholds were comparable to those calculated previously (-20 to 14-fold change). Confidence intervals for both marine and freshwater thresholds remained wide. The doubling of the database increases the value of ToMEx for researchers, particularly those focused on characterizing hazards associated with microplastics. Its utility remains limited for environmental managers as 89% of studies in ToMEx 2.0 failed to meet minimum screening criteria for threshold derivation, highlighting the need to generate fit-for-purpose toxicity data for threshold development. However, ToMEx continues to be a useful research tool, and future iterations could become even more powerful through novel artificial intelligence applications to streamline data curation and even predict toxicological outcomes. Supplementary Information: The online version contains supplementary material available at 10.1186/s43591-025-00145-6.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".