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Record W4387220835 · doi:10.1002/jha2.786

Scientific techniques in adolescent and young adult classic Hodgkin lymphoma

2023· review· en· W4387220835 on OpenAlexafffund
Francesco Maura, Tomohiro Aoki

Bibliographic record

VenueeJHaem · 2023
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Cancer InstituteCanadian Institutes of Health ResearchSylvester Comprehensive Cancer Center, University of Miami Health SystemsLeukemia and Lymphoma SocietyLymphoma Research Foundation
KeywordsLymphomaHodgkin lymphomaGenomicsMedicineMedical physicsComputational biologyGenomeBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Understanding the tumor microenvironment and genomic landscape is crucial for better prediction of treatment outcomes and developing novel therapies in Hodgkin lymphoma (HL). Recent advancements in genomics have enabled researchers to gain deeper insights into the genomic characteristics of HL at both single-cell resolution and the whole genome level. The use of noninvasive methods such as liquid biopsies and formalin-fixed paraffin-embedded-based imaging techniques has expanded the possibilities of applying cutting-edge analyses to routine clinically available samples. Collaborative efforts between adult and pediatric group are imperative to translate novel findings into routine patient care.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.073
GPT teacher head0.357
Teacher spread0.284 · 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.

Study designOther design
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

Citations3
Published2023
Admission routes2
Has abstractyes

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