Anti-icing properties of polar bear fur
Bibliographic record
Abstract
) is the only Arctic land mammal that dives into water to hunt. Despite thermal insulation provided by blubber and fur layers and low Arctic temperatures, their fur is typically observed to be free of ice. This study investigates the anti-icing properties of polar bear fur. Here, we show that polar bear fur exhibits low ice adhesion strengths comparable to fluorocarbon-coated fibers, with the low ice adhesion a consequence of the fur sebum (hair grease). Lipid analyses reveal the presence of cholesterol, diacylglycerols, anteisomethyl-branched fatty acids, and the unexpected absence of squalene. Quantum chemical calculations predict low ice adsorption energies for identified lipids and high adsorption for squalene, suggesting that sebum composition is responsible for the observed anti-icing properties. Our work enhances understanding of polar bears and their interactions with their environment and builds on Inuit knowledge of natural anti-icing materials.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".