A Method to Assess the Quality of Studies That Examine the Toxicity of Engineered Nanomaterials
Bibliographic record
Abstract
As reports on the safety of various nanomaterials have yielded conflicting results, assessment of the reliability of each study is required to objectively interpret overall safety of the nanomaterial. A 2-step method to assess the quality of nanotoxicity studies is described. The first step uses a publicly available tool to rank the reliability of the study based on adequacy of design and documentation of methods, materials, and results, providing a "study score." The second step determines the completeness of physicochemical characterization of the nanomaterial/nanomaterials assessed within the study, providing a "nanomaterial score." This approach is encouraged to promote the notion that for studies conducted with nanomaterials, the combination of a reliable study and sufficient nanomaterial characterization is of significantly greater value than either of these alone. It is anticipated that the use and evolution of this approach will assist with the design and interpretation of studies assessing nanomaterial toxicity.
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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 | 0.244 | 0.306 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.026 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".