Principles and Operational Parameters to Optimize Poison Removal with Extracorporeal Treatments
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
A role for nephrologists in the management of a poisoned patient involves evaluating the indications for, and methods of, enhancing the elimination of a poison. Nephrologists are familiar with the various extracorporeal treatments (ECTRs) used in the management of impaired kidney function, and their respective advantages and disadvantages. However, these same skills and knowledge may not always be considered, or applicable, when prescribing ECTR for the treatment of a poisoned patient. Maximizing solute elimination is a key aim of such treatments, perhaps more so than in the treatment of uremia, because ECTR has the potential to reverse clinical toxicity and shorten the duration of poisoning. This manuscript reviews the various principles that govern poison elimination by ECTR (diffusion, convection, adsorption, and centrifugation) and how components of the ECTR can be adjusted to maximize clearance. Data supporting these recommendations will be presented, whenever available.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it