Bioremediation of Fracking: Novel Hybrid Biofilm System Using Synthetically Engineered Curli Fibres
Bibliographic record
Abstract
Hydraulic fracturing, a popular mining technique, generates heavy metal contamination in nearby freshwater aquifers. This poses a threat to both the surrounding ecosystems and human health if exposed. Existing methods of heavy metal removal can produce additional hazardous byproducts. This proposal presents the use of a hybrid biofilm filter containing graphene and curli fibres with metal binding sites. Curli fibres are amyloid fibrils found on the extracellular biofilm of Escherichia coli (E. coli). Through the use of plasmid vectors, E. coli will be engineered to produce secreted curli fibres with metal-binding residues. The stability and cohesive properties of the curli fibres augments the adherence to the graphene scaffolding, thus allowing for generation of a hybrid biofilm. With the filtration design and various experimental controls proposed, this model is ready for empirical proof of concept and subsequent quantitative optimization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 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".