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Record W2617733729 · doi:10.17925/ohr.2017.13.01.41

Paraneoplastic Syndromes in Children with Hodgkin Lymphoma

2017· article· en· W2617733729 on OpenAlexaff
Laura Betcherman, Angela Punnett

Bibliographic record

VenuetouchREVIEWS in Oncology & Haematology · 2017
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineMalignancyLimbic encephalitisLymphomaHodgkin lymphomaPathophysiologyPathologyAntibodyImmunologyAutoantibody

Abstract

fetched live from OpenAlex

Paraneoplastic syndromes (PNS) refer to a phenomenon whereby certain malignancies manifest as symptoms not directly related to the tumor itself. PNS has been described in association with Hodgkin lymphoma (HL) in adults and children and may affect a number of organ systems. The pathophysiology is variable and in many cases is not well understood. Specific paraneoplastic antibodies have been isolated in some syndromes, though are not required for the diagnosis. The two best described for HL are the anti-Tr and anti-mGluR5 antibodies identified in some cases of limbic encephalitis and cerebellar degeneration respectively. A high index of suspicion for underlying malignancy is necessary when recognizing these clinical syndromes to avoid a diagnostic delay. Successful treatment of the HL often reverses the manifestations of PNS although organ function at diagnosis may limit therapeutic options. Some patients suffer devastating complications of their PNS.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.344
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2017
Admission routes1
Has abstractyes

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