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 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 | 0.005 | 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 | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".