Information theoretic measures of perinatal cardiotocography synchronization
Bibliographic record
Abstract
We examined the use of bivariate mutual information (MI) and its conditional variant transfer entropy (TE) to address synchronization of perinatal uterine pressure (UP) and fetal heart rate (FHR). We used a nearest-neighbour based Kraskov entropy estimator, suitable to the non-Gaussian distributions of the UP and FHR signals. Moreover, the estimates were robust to noise by use of surrogate data testing. Estimating degree of synchronicity and UP-FHR delay length is useful since they are physiological correlates to fetal hypoxia. Mutual information of the UP-FHR discriminated normal and pathological fetuses early (160 min before delivery) and discriminated normal and metabolic acidotic fetuses slightly later (110 min before delivery), with higher mutual information for progressively pathological classes. The delay in mutual information transfer was also discriminating in the last 50 min of labour. Transfer entropy discriminated normal and pathological cases 110 min before delivery with lower TE values and longer information transfer delays in pathological cases, to our knowledge, the first report of this phenomena in the literature.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".