Peripheral pacemakers and patterns of slow wave propagation in the canine small intestine in vivo
Bibliographic record
Abstract
In an anesthetized, open-abdomen, canine model, the propagation pattern of the slow wave and its direction, velocity, amplitude, and frequency were investigated in the small intestine of 8 dogs. Electrical recordings were made using a 240-electrode array from 5 different sites, spanning the length of the small intestine. The majority of slow waves propagated uniformly and aborally (84%). In several cases, however, other patterns were found including propagation in the oral direction (11%) and propagation block (2%). In addition, in 69 cases (3%), a slow wave was initiated at a local site beneath the electrode array. Such peripheral pacemakers were found throughout the entire intestine. The frequency, velocity, and amplitude of slow waves were highest in the duodenum and gradually declined along the intestine reaching lowest values in the distal ileum (from 17.4+/-1.7 c/min to 12.2+/-0.7 c/min; 10.5+/-2.4 cm/s to 0.8+/-0.2 cm/s, and 1.20+/-0.35 mV to 0.31+/-0.10 mV, respectively; all p<0.001). Consequently, the wavelength of the slow wave was strongly reduced from 36.4+/-0.8 cm to 3.7 +/- 0.1 cm (p<0.001). We conclude that the patterns of slow wave propagation are usually, though not always, uniform in the canine small intestine and that the gradient in the wavelength will influence the patterns of local contractions.
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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 | 0.000 | 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 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".