Cellulose-Based Biosensors for Esterase Detection
Bibliographic record
Abstract
Cellulose has emerged as an attractive\nsubstrate for the production\nof economical, disposable, point-of-care (POC) analytical devices.\nDevelopment of novel methods of (bio)activation is central to broadening\nthe application space of cellulosic materials. Ironically, such efforts\nare stymied by the inherent biocompatibility and recalcitrance of\ncellulose fibers. Here, we have elaborated a versatile, chemo-enzymatic\napproach to activate cellulosic materials for CuAAC “click\nchemistry”, to develop new fluorogenic esterase sensors. Gentle,\naqueous modification conditions facilitate broad applicability to\ncellulose papers, gauzes, and hydrogels. Tethering of the released\nfluorophore to the cellulose surface prevents signal degradation due\nto diffusion and enables straightforward, sensitive visualization\nwith a simple light source in resource-limited situations.
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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) | 0.012 | 0.001 |
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; both teacher heads 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".