Isothiazolinones Common in Children's Toy Slime
Bibliographic record
Abstract
BACKGROUND: Contact dermatitis to homemade slime has been frequently reported, with isothiazolinones as a likely sensitizer. Little is known on the presence of these preservatives in commercial, store-bought slime products. OBJECTIVES: The aims of the study were to review the literature on "slime dermatitis" and to assess for the presence of isothiazolinones in commercially available slime products and homemade slime components. METHODS: An experimental, colorimetric spot test was used to verify the presence of isothiazolinones in 38 slime products of the 16 best-selling commercial slime kits, 1 finished homemade slime, and 4 common components of homemade slime. High-performance liquid chromatography with UV detection was performed on 8 commercial slime products. RESULTS: According to the spot test, 27 (71%) of the 38 commercial slime products contained isothiazolinones. High-performance liquid chromatography with UV detection analyses indicated, however, that false-positives and false-negatives readily occur: isothiazolinone content was correctly identified in only 4 (50%) of the 8 samples. CONCLUSIONS: This study is the first to demonstrate the presence of isothiazolinones in commercial slime toys. Although the colorimetric spot test may have some utility as a screening assay, it is far from specific and likely not sensitive enough to reliably identify methylisothiazolinone.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".