Design of a microvolumetric blood counter/sampler for metabolic PET imaging in rats and mice
Bibliographic record
Abstract
Quantitative metabolic imaging in small animals with positron emission tomography (PET) requires the determination of the tracer concentration in whole blood, arterial plasma and metabolites as a function of time. A blood counting and sampling system was designed to simultaneously measure the time-activity curve as microvolumes of blood are collected. The system consists of a flow-through counter made of a plastic scintillator to detect positrons and of a computer-controlled blood sampler based on the concept of bubble segmentation. The number and size of samples, the withdrawal speed and the sampling time are all programmable and can be modified on-line. Samples as small as 10 /spl mu/l can be repetitively obtained from an implanted arterial catheter in the femoral vein or artery of small rats (150 g) or the jugular vein of mice (20 g). For medium sampling speed (100 /spl mu/l/min) at a constant rate, the standard deviation of the sample activity is typically less than 4%. By cutting the tubing at the bubbles at the end of the experiment, samples are made available for further processing and biochemical analysis. This apparatus has become an essential tool for quantitative animal PET studies, allowing easy, reliable sampling at a low cost.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".