High Frequency Ultrasound Signal Statistics From Mouse Mammary Tissue During Involution
Bibliographic record
Abstract
We investigate the use of signal envelope statistics to monitor the tissue restructuring process during mouse mammary tissue involution. Using an f/3 transducer operating at a centre frequency of 20 MHz, ultrasound backscatter data were collected from mouse mammary tissue following removal of the litter. The signal envelope statistics were examined by fitting the Rayleigh and generalized gamma distributions. The goodness of fit of the distributions was evaluated by the Kolmogorov-Smirnov test. The goodness of fit of the Rayleigh distribution increased to a maximum at day 3 of involution, roughly corresponding to the peak of apoptosis in the tissue. Similarly, the fit parameters of the generalized gamma distribution indicate that at day 3 the distribution is most Rayleigh like. It is believed that the condensation of the nucleus and reorganization of the tissue structure produced these changes in the statistics of the signal envelope. The results demonstrate that high frequency ultrasound signal envelope statistics can be applied to monitor changes to tissue structure in vivo.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".