<scp>Water‐repellent</scp> films from corn protein and tomato cutin
Bibliographic record
Abstract
Abstract Flexible and hydrophobic biobased films were obtained using zein esterified with methanol and para ‐toluene ( p ‐toluene) sulfonic acid, cutin from tomato peels and ethanol. Esterification was confirmed by proton nuclear magnetic resonance and attenuated total reflectance–Fourier transform infrared spectroscopy (ATR‐FTIR). Non‐modified zein films were brittle and hydrophilic. ATR‐FTIR demonstrated that zein esterification increased zein hydrophobicity. Without cutin, esterified zein films were hydrophobic but brittle. Addition of cutin yielded films that were flexible and hydrophobic, as demonstrated by contact angle measurements. Principal component analysis (PCA) of ATR‐FTIR data showed that intensities at 3195 cm −1 and 3490 cm −1 were correlated to the relative hydrophobicity of zein films. PCA also showed that films of esterified zein and cutin were more hydrophobic than their counterparts (non‐modified zein without cutin). Optical and scanning electron microscopy demonstrated that esterified zein was compatible with cutin and yielded cohesive films, which did not fracture upon bending.
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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) | 0.001 | 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".