Bibliographic record
Abstract
Frogs are particularly vulnerable to the effects of chemical pollutants due to their high sensitivity to the environment. One class of chemical that may endanger frogs are the phthalate esters, which are commonly used as plasticizers in plastic manufacturing to impart flexibility to vinyl products. Because of this, phthalates are widely produced and distributed. However, since they are not covalently bound to the plastic matrix, phthalates tend to leach into surrounding environments. Phthalate contamination has been ubiquitously detected in aquatic environments, so it is important to understand its effects. This study analysed the lethal and sub-lethal effects of diisoheptyl phthalate (DIHepP) and diisononyl phthalate (DINP), two phthalates that are currently under assessment by Environment Canada due to the lack of data on their effects. To test this, embryos of the frog Silurana tropicalis were exposed to varying concentrations of both phthalates during early embryonic development. Preliminary data suggests that neither DIHepP nor DINP affect embryo mortality at concentrations up to 30 ppm and 10 ppm, respectively. To investigate the effect of these phthalates on development, embryos have been scored for malformations. Sub-lethal effects have been determined by quantifying the expression of hormone axis genes in exposed embryos. Through these observations, both system-wide and cellular effects of these phthalates have been elucidated. Overall, this study provides valuable insight on the effects of DIHepP and DINP to aid in the assessment of the risk that these compounds may pose to frogs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".