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Neurologic complications of leukemia

2002· article· en· W4251645486 on OpenAlexaff
Alexis Demopoulos, Lisa M. DeAngelis

Bibliographic record

VenueCurrent Opinion in Neurology · 2002
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsLeukemia & Lymphoma Society of Canada
Fundersnot available
KeywordsMedicineLeukemiaIntensive care medicineCentral nervous systemChemotherapyPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Purpose of review As treatment of the leukemias improves, patients are surviving longer. Recognizing and rapidly treating metastatic complications or avoiding neurotoxic therapies improves outcome, reduces morbidity and mortality, and limits long-term sequelae. Recent findings Neurologic dysfunction may result from leukemic infiltration of the nervous system or as a consequence of chemotherapy or prophylactic craniospinal irradiation. The present review summarizes common problems in the neurologic complications of leukemia and discusses recent advancements in their diagnosis and treatment. Summary Topics covered in detail include central nervous system prophylaxis, leptomeningeal metastasis, and common hematologic complications affecting the brain. The findings aid in the clinical management of patients with leukemia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.108
GPT teacher head0.346
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2002
Admission routes1
Has abstractyes

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