AXISYMMETRIC DROP SHAPE ANALYSIS (ADSA) FOR THE DETERMINATION OF SURFACE TENSION AND CONTACT ANGLE
Bibliographic record
Abstract
A drop shape analysis technique called Axisymmetric Drop Shape Analysis (ADSA) has been developed in our laboratory over the last twenty years. ADSA is a powerful technique for the measurement of interfacial tensions and contact angles of pendant drops, sessile drops, and bubbles. In essence, it relies on the best fit between theoretical Laplacian curves and an experimental profile. Despite the general success of ADSA, deficient results may be obtained for drops close to spherical shape. Since the sources of these limitations were unknown, the entire ADSA technique, including hardware and software, has been reviewed. The key element of the new generation of ADSA is the modularization of the software, because a firm fixed package would not be suitable for all experimental situations. Another novel feature of the methodology is the development of a quantitative criterion, i.e., a shape factor, that determines the range of drop shapes, in which ADSA succeeds or fails.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".