Bibliographic record
Abstract
The swelling behavior of the elastin network has been investigated by comparing the linear expansion of samples of purified elastin with the volume expansion of the network, calculated on the basis of composition. Elastin sample dimensions and sample masses were measured under three conditions in which volume changes: thermal expansion at fixed water contents, deswelling due to dehydration, and swelling to greater than normal levels due to the swelling agent, sodium dodecyl sulfate. Isotropic network swelling usually changes length in proportion to the cube root of network volume, but length was found to be directly proportional to volume, showing a greater increase in length than expected. This unusual swelling behavior is attributed to an unusual elastin structure at the subfiber level, but there is insufficient detail on elastin's molecular organization to identify a mechanism to explain how it occurs. Assuming the network swells homogeneously, we describe two models that correctly predict swelling behavior, but these models imply a significant deviation from the structure generally assumed for an elastomeric polymer network of kinetically free molecular chains. Assuming that the network swells heterogeneously removes part of the difficulty with the models, but the observed direct proportionality between length and network volume remains to be explained.
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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) | 0.000 | 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 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".