MétaCan
Menu
Back to cohort
Record W2414415814 · doi:10.1007/s00277-016-2722-y

Non-anaplastic peripheral T cell lymphoma in children and adolescents—an international review of 143 cases

2016· article· en· W2414415814 on OpenAlexaff
Karin Mellgren, Andishe Attarbaschi, Oussama Abla, Sarah Alexander, Simon Bomken, Eva Bubanská, Aks Chiang, Monika Csóka, Alina Fedorova, Edita Kabíčková, L. Kapuscinska-Kemblowska, Ryōji Kobayashi, Zdenka Křenová, Friederike Meyer‐Wentrup, Natalia Miakova, Marta Pillon, Geneviève Plat, Anne Uyttebroeck, Denise Williams, Grażyna Wróbel, Udo Kontny

Bibliographic record

VenueAnnals of Hematology · 2016
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsHospital for Sick Children
FundersBarncancerfondenNational Institute for Health and Care Research
KeywordsMedicineAnaplastic large-cell lymphomaPeripheral T-cell lymphomaLymphomaInternal medicineNot Otherwise SpecifiedHematologyT-cell lymphomaRetrospective cohort studyLarge cellT cellPediatricsOncologyGastroenterologyCancerImmunology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.353
Teacher spread0.325 · 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 designObservational
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

Citations60
Published2016
Admission routes1
Has abstractno

Explore more

Same venueAnnals of HematologySame topicCutaneous lymphoproliferative disorders researchFrench-language works237,207