Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study of wetting characteristics of low-energy (e.g., superhydrophobic) liquid-repellent surfaces is of great importance towards optimal design of such micro/nano-engineered surfaces. The most common technique to accomplish this involves bringing a drop generated at the needle-tip close to the characterizing substrate with a goal to deposit it on the substrate, which often becomes a challenge when the surface energy of the drop-substrate combination is comparable to the needle-drop system. In this paper, we proposed a new “needle-free” drop deposition technique, which overcomes this challenge for characterization the low-energy substrates. This is achieved by placing an additional low-energy substrate above the characterizing substrate and allowing the drop-needle combination to impact on this additional substrate. This technique is not only independent of the wetting properties of the needle and the characterizing substrate but is also independent of the liquid drop properties, thereby making it a very universal technique for characterizing substrate in air medium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.105 |
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 it