Interaction of <scp>l</scp>‐leucyl‐<scp>l</scp>‐leucyl‐<scp>l</scp>‐leucine thin film with water and organic vapors: receptor properties and related morphology
Bibliographic record
Abstract
The ability of highly ordered tripeptide structures to keep or change their morphology in contact with organic vapors was studied. A thin film of tripeptide L-leucyl-L-leucyl-L-leucine (LLL) was prepared having microcrystals and nanocrystals on its surface, which are stable upon vacuum drying but become objects of selective morphology change after a contact with vapors of organic solvents. Fine separate LLL crystals and their agglomerates of submicron and larger dimensions were observed by atomic force microscopy and scanning electron microscopy. After saturation with guest vapors, these crystals can remain intact or change their morphology with the increase in size or complete destruction depending on the guest molecular structure. The crystals completely lose their shape after the binding of pyridine vapors. The other studied guests produce much smaller transformations or have no effect on crystal morphology despite being sorbed by solid LLL, which was shown using quartz crystal microbalance sensor. The observed size-exclusion effect for guest sorption by LLL was found to be broken by the same guests that can change the initial crystal shape. This helps to explain the morphology changes of LLL crystals after the guest sorption and release.
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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) | 0.001 | 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 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".