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Record W3088143182 · doi:10.1002/pbc.28702

Guidance regarding COVID‐19 for survivors of childhood, adolescent, and young adult cancer: A statement from the International Late Effects of Childhood Cancer Guideline Harmonization Group

2020· article· en· W3088143182 on OpenAlexaff
Lisanne C. Verbruggen, Yuehan Wang, Saro H. Armenian, Matthew J. Ehrhardt, Helena J. H. van der Pal, Elvira C van Dalen, Jorrit W van As, Edit Bárdi, Katja Baust, Claire Berger, Elio Castagnola, Katie A. Devine, Judith Gebauer, Jordan Gilleland Marchak, Adam Glaser, Andreas H. Groll, Gabrielle M. Haeusler, Jaap den Hartogh, Riccardo Haupt, Lars Hjorth, Miho Kato, Tomáš Kepák, Maria M.W. Koopman, Thorsten Langer, Miho Maeda, Gisela Michel, Monica Muraca, Paul C. Nathan, Selina R. van den Oever, Vesna Pavasovic, Satomi Sato, Fiona Schulte, Lillian Sung, Wim J. E. Tissing, Anne Uyttebroeck, Renée L. Mulder, Claudia E. Kuehni, Roderick Skinner, Melissa M. Hudson, Leontien C.M. Kremer

Bibliographic record

VenuePediatric Blood & Cancer · 2020
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of TorontoUniversity of CalgaryHospital for Sick Children
Fundersnot available
KeywordsMedicineGuidelineHarmonizationChildhood cancerCancerCoronavirus disease 2019 (COVID-19)MEDLINEFamily medicineYoung adultStatement (logic)Survivorship curvePediatric cancerPediatricsGerontologyDiseasePathologyInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Childhood, adolescent, and young adult (CAYA) cancer survivors may be at risk for a severe course of COVID-19. Little is known about the clinical course of COVID-19 in CAYA cancer survivors, or if additional preventive measures are warranted. We established a working group within the International Late Effects of Childhood Cancer Guideline Harmonization Group (IGHG) to summarize existing evidence and worldwide recommendations regarding evidence about factors/conditions associated with risk for a severe course of COVID-19 in CAYA cancer survivors, and to develop a consensus statement to provide guidance for healthcare practitioners and CAYA cancer survivors regarding COVID-19.

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)0.024
metaresearch head score (Gemma)0.064
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0050.004
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0050.003

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 head0.019
GPT teacher head0.302
Teacher spread0.282 · 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
GenreEditorial

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

Citations31
Published2020
Admission routes1
Has abstractyes

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