High-throughput analysis of multiple stress pathways using GFP reporters in<i>C. elegans</i>
Bibliographic record
Abstract
Stress-responsive genes belonging to multiple defensive pathways in the nematode C. elegans are cross-regulated by kinase signalling (AKT-1/-2, p38 MAPK) and transcription factors (DAF-16, SKN-1). This cross-talk between stress pathways implies that they are best regarded as a stress-response network (SRN), whose behaviour as a whole should be amenable to mathematical modelling. We have used GFP reporter strains to provide a rapid readout of expression levels for 24 genes, representing principal outputs and transcription factors in the heat-shock, metal-binding, oxidative stress, phase I & phase II detoxification, and genotoxic stress pathways. Acute toxicity data (up to ~24 h) has been generated for selected metal (presented here) and pesticide toxicants across a wide range of doses, and common response patterns identified. Mathematical modelling of these response data, informed by an understanding of the underlying genetic circuitry, should allow our model to predict the likely toxicity of pollutant mixtures. Future work will test the accuracy of such predictions, leading to an iterative process of model refinement.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".