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
A number of new imaging methods have been developed specifically for use with ultrasound contrast agents. These methods rely on the peculiar behavior of microbubbles in an ultrasound field. At low incident acoustic pressures (reflected by the mechanical index, MI) microbubbles emit harmonics. These can be detected using harmonic or pulse inversion imaging. At higher MI, bubbles are disrupted, emitting a strong, nonlinear echo. Harmonic power Doppler methods are able to detect this echo, offering the most sensitive method for the detection of microbubble at the perfusion level. Although the first images of myocardial perfusion were made using this disruption method, it requires intermittent imaging with interframe intervals of up to 6 heart beats. Pulse inversion Doppler imaging is a newer method that is able to detect the nonlinear component of bubble echoes at a very low MI, thereby making possible real-time myocardial perfusion imaging. An understanding of the behavior of bubbles during an imaging examination is an essential prerequisite to its success in clinical practice.
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) | 0.004 | 0.011 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it