Flow Cytometry Approach for the Identification of Liposomal Cytarabine Toxicity
Bibliographic record
Abstract
Neurological complications may develop either at diagnosis or during the course of many hematological malignancies after initiation of therapy. The etiology might be very different but, once infection is excluded, differential diagnosis is mainly focused on distinguishing between leptomeningeal progression and toxicity secondary to therapy. In each case, the subsequent clinical decision would be completely opposite. Contrast central nervous system magnetic resonance, biochemistry, serology and cultures of the cerebrospinal fluid, and electromyography are usually performed in these patients, but demonstration of toxicity remains a diagnosis of exclusion for reagents such as liposomal cytarabine. Based on the experience of 2 clinical cases, we reviewed a database of immunophenotypic studies of the cerebrospinal fluid, and then we summarize how to use flow cytometry to positively support liposomal cytarabine toxicity. J Neurol Res. 2012;2(2):48-53 doi: https://doi.org/10.4021/jnr95w
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".