Differential Scanning Fluorimetry provides high throughput data on silk protein transitions.
Bibliographic record
Abstract
Here we present a set of measurements using Differential Scanning Fluorimetry (DSF) as an inexpensive, high throughput screening method to investigate the folding of silk protein molecules as they abandon their first native melt conformation, dehydrate and denature into their final solid filament conformation. Our first data and analyses comparing silks from spiders, mulberry and wild silkworms as well as reconstituted 'silk' fibroin show that DSF can provide valuable insights into details of silk denaturation processes that might be active during spinning. We conclude that this technique and technology offers a powerful and novel tool to analyse silk protein transitions in detail by allowing many changes to the silk solutions to be tested rapidly with microliter scale sample sizes. Such transition mechanisms will lead to important generic insights into the folding patterns not only of silks but also of other fibrous protein (bio)polymers.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".