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
Speed of sound and acoustic wave attenuation are sensitive to fluid phase composition and to the presence of liquid-liquid interfaces. In this work, the use of an acoustic array comprising 64 elements as a non-intrusive sensor for liquid-liquid interface, phase separation kinetics measurement in bulk fluids, and local composition measurement in porous media is illustrated. Three benchmark examples: the phase behaviour of methanol + mixed hexanes and methanol + heptane mixtures at 25.0 °C and 1 bar, and Athabasca bitumen + heptane in a synthetic silica porous medium at 22.5 °C and 1 bar, illustrate the accuracy of liquid-liquid interface and potential research and industrial applications of the technique. Liquid-liquid interfaces can be detected independently using both speed of sound and acoustic wave attenuation measurements. The precision of the interface location measurement is 300 μm. As complete scans can be performed at a rate of 1 Hz, phase separation kinetics and diffusion of liquids within porous media are readily tracked. The technique is expected to find application where the fluids or porous media are opaque to visible light and where other imaging techniques are not readily applied, or are too costly. A current limitation is that the acoustic probes must be cooled to less than 315 K in order for them to operate.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.028 |
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