Dynamic topographic mapping of the human bladder during voiding using functional near-infrared spectroscopy
Bibliographic record
Abstract
Functional near-infrared spectroscopy (fNIRS) with multichannel instruments and grids of source-detector pairs can map regional change in oxygenation/hemodynamics. Developed for cortical brain mapping, fNIRS technology has relevance in other organs where pathology affects the microcirculation. We describe fNIRS of the human bladder for evaluation of hemodynamic change during voiding. A 5x5-cm grid with two source-detector pairs is placed on the abdomen suprapubically in an asymptomatic male. In four separate trials, after natural bladder filling NIRS-derived changes in oxyhemoglobin (O(2)Hb), deoxyhemoglobin (HHb), and total hemoglobin (tHb) concentration are recorded during voiding (measured via uroflow), using four channels of a four wavelength continuous wave instrument. Graphic and video images (topographic mapping software) are generated. Changes in tHb occur following permission to void that predominantly reflected variation in O(2)Hb; tHb peaks at maximum urine flow then falls to a nadir lasting to uroflow end. Change in fNIRS video color intensity correlates with graphic change in chromophore concentration. Color variations across the mapped area suggest regional hemodynamic variation. fNIRS bladder studies generate reproducible chromophore data consistent with single channel studies, but the dynamic color video and larger tissue area monitored potentially offer new methodology for investigating regional variations in bladder oxygenation and hemodynamics.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".