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Screening for SARS-COV-2 infection in pediatric oncology patients during the epidemic peak in Italy

2020· preprint· en· W3036593424 on OpenAlexaff
Simone Cesaro, Francesca Compagno, Daniele Zama, Linda Meneghello, Nagua Giurici, Elena Soncini, Daniela Onofrillo, Federico Mercolini, Rosamaria Mura, Katia Perruccio, Raffaela De Santis, Antonella Colombini, Angelica Barone, Valentina Baretta, Mariagrazia Petris

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakMedicinePediatric oncologyVirologyInternal medicineOncologyPediatricsIntensive care medicineCancerOutbreakInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

SARS-COV-2 infection can be asymptomatic or mildly symptomatic. The effect of chemotherapy on an asymptomatic infected patient is unknown. Three hundred-thirty-four and 56 NFS were performed as screening for SARS-CoV-2 infection in 247 and 34 pediatric patients undergoing chemotherapy and stem cell transplantation, respectively. NFS was positive in 10 patients. All positive patients withdrew from chemotherapy. Nine patients became negative. One patient is still positive after 38 days.The identification of asymptomatic SARS-COV-2 infection is important to reduce the hospital spread of infection. Further studies are needed to define the least risky management of chemotherapy in asymptomatic SARS-CoV-2 patients.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.161
GPT teacher head0.446
Teacher spread0.286 · 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
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

Citations3
Published2020
Admission routes1
Has abstractyes

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