Hydra, a model system for environmental studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hydra have been extensively used for studying the teratogenic and toxic potential of numerous toxins throughout the years and are more recently growing in popularity to assess the impacts of environmental pollutants. Hydra are an appropriate bioindicator species for use in environmental assessment owing to their easily measurable physical (morphology), biochemical (xenobiotic biotransformation; oxidative stress), behavioural (feeding) and reproductive (sexual and asexual) endpoints. Hydra also possess an unparalleled ability to regenerate, allowing the assessment of teratogenic compounds and the impact of contaminants on stem cells. Importantly, Hydra are ubiquitous throughout freshwater environments and relatively easy to culture making them appropriate for use in small scale bioassay systems. Hydra have been used to assess the environmental impacts of numerous environmental pollutants including metals, organic toxicants (including pharmaceuticals and endocrine disrupting compounds), nanomaterials and industrial and municipal effluents. They have been found to be among the most sensitive animals tested for metals and certain effluents, comparing favourably with more standardised toxicity tests. Despite their lack of use in formalised monitoring programmes, Hydra have been extensively used and are regarded as a model organism in aquatic toxicology.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it