WHAT “BLOOD VOLUME” DO WE DIALYZE?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Blood volume changes [BV] during hemodialysis [HD] can be done by optical monitoring of hematocrit [het] eg by Crit-Line monitor. The hct differs in different parts of the body. The arterial hct is established after blood is mixed in the right heart. Only in the cardiopulmonary circuit [CP] is the hct uniform and representative of the value measured in the arterial HD line. □BV by Crit-line may only measure □CP volume. The “central blood volume” [CBV] is defined as the volume of blood in the heart, great vessels and lung capillaries and can be measured by indicator dilution methods during dialysis [Transonic HD monitor] from the cardiac output [CO] and the indicator transit time. Changes in □BV and CBV should be similar. The interrelationships of □BV and CBV plus those of CO were tested during HD following periods of UF and then subsequent vascular compartment refilling [R]. UF sufficient to cause □BV of-6.7%[±2.4;n=21] was associated with a reduction in CBV by 0.1L [±0.2] [relative fall 3.75%] and in CO of 0.94 L/min [± 1.8] [relative fall 10.5%]. The changes in these parameters all significantly correlated [r=min 0.46, p=min 0.012]. Following R to a □BV increase of 2.4% [± 1.3, n=11] CBV increased by 0.31 L [± 0.39], a relative change of +22% and CO by 1.07 L/min [±1.61] a change of +26%. The CBV and CO changes correlated [r=0.86, p=0.001] but all correlations with □BV were lost. These data suggest □BV and CBV refer to different “blood volumes” with changes moving in the same direction but at different rates. Changes in CO are closer related to changes in CBV than ± BV.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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 it